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Heavy metals such as Lead(II), Nickel(II), Manganese(II), Cadmium(II), Chromium(VI), etc., are leached from the coal ash of thermal power plants. These metals contaminate ash pond water and subsequently contaminate groundwater. Phycoremediation using microalgae/cyanobacteria is an emerging technology for removal of heavy metals. The present study aims at phycoremediation of the said heavy metals from ash pond water using cyanobacterial consortium of Limnococcus limneticus and Leptolyngbya subtilis followed by the development of an accurate data-driven Multigene Genetic Programing (MGGP) approach for modeling and optimization of the process. The developed model was used to obtain a correlation between the average removal of metals and biomass production with all input factors such as the initial metal concentrations, pH, and days of incubation. To maximize metal removal and biomass production, the Water Evaporation Optimization (WEO) technique was applied to determine optimal values of input parameters. The application of WEO for the optimization of the phycoremediation process is the first of its kind and here lies the novelty of the study. [ABSTRACT FROM AUTHOR]

Heavy metals such as Lead(II), Nickel(II), Manganese(II), Cadmium(II), Chromium(VI), and others are leached from coal ash in thermal power plants, contaminating ash pond water and subsequently contaminating groundwater. Phycoremediation using microalgae or cyanobacteria is an emerging technology to remove such heavy metals from ash pond water. The present study aims at development of an accurate data-driven Genetic Programing (GP) approach for modelling of the phycoremediation process for abatement of the above-mentioned heavy metals using a consortium comprising of a cyanobacterium Synechococcus sp. and green algae Chlorella sp. The developed model was used to find a relation between the average percentage removal of metals with all input parameters such as the initial metal concentrations, pH, and days. To maximise metal removal, Genetic Algorithm (GA) optimisation technique was applied to determine optimal values of input parameters. These optimum input parameters are difficult to get through experimentation using the trial and error method. The established modelling and optimisation technique is generic and can be applied to any other experimental study. [ABSTRACT FROM AUTHOR]

One of the essential tasks of the modern fishery is to integrate fishery‐based tourism with it as a part of sustainable development. Here, we propose and study a two‐species fishery model where the ecological and economic concepts are integrated. The objectives are to demonstrate the effect of fishing tax and tourist entrance fees to stabilize fishery dynamics and maximize revenue generation. For this, we consider a predator–prey fishery model coupled with dynamic harvesting and time‐dependent fish price variation. The prey fish is commercially harvested, and the predatory fish is used for recreation purposes of the visitors with an entry fee. A fishing tax is levied on the fishers to restrict the overfishing of this renewable resource. We provide the local and global stability conditions of different equilibrium points of the system and unveil the broader dynamics through bifurcation analysis. Pontryagin's maximum principle shows the existence of an optimal fishing tax that maximizes overall revenue generation. [ABSTRACT FROM AUTHOR]

The growth of renewable energy actively takes part in decarbonizing the fossil-fuel-based energy system. It reduces carbon emissions, carbon footprint, and greenhouse gas emissions and increases clean energy. The usage of renewable resources reduces and solves several problems, such as increasing temperature, carbon footprint, greenhouse gas emissions, and energy waste. Every sector contributes to increasing the above-mentioned factors in the environment. One of the main reasons for this biodegradation and climate change is energy resources. Using renewable energy instead of fossil fuel can solve the problem. This paper aims to find open research problems about the application of renewable energy and to initiate new innovative ideas regarding renewable energy. A detailed state of the art includes trends for renewable energy resources, their theoretical evolution, and practical implementations. Methodologies used for decision analysis in renewable energy are discussed in detail. The time frame for this analysis of renewable energy is 2010 to >2022. An extensive literature review finds a huge research scope in applying renewable energy in other research, such as logistics, smart production management, and advanced inventory management. Then, major changes in the profit/cost of that system due to renewable energy can be analyzed. This research proposes some innovative new ideas related cost formulas for renewable energy for the corresponding open problems. [ABSTRACT FROM AUTHOR]

In thermal power plants, ash pond water is being polluted with heavy metals such as Lead (II), Nickel (II), Manganese (II), Cadmium (II), Chromium (VI), and so on, through leaching from coal ash and this can eventually contaminate the groundwater. In the present study, a consortium consisting of a cyanobacterium Synechococcus sp. and green algae Chlorella sp. was used for phycoremediation of such heavy metals from simulated ash pond water. The concentrations of metals, pH and days were varied during experimentation. An accurate data‐driven artificial neural network (ANN) model was developed with the experimental data to find a relation between the input variables of the phycoremediation process with the percentage removal of the pollutants and amount of biomass produced. The optimum ANN design and ANN algorithm were evaluated using an automatic exhaustive search technique. To maximize metal removal and biomass production, a hybrid artificial neural network‐simulated annealing (ANN‐SA) optimization technique was applied to determine optimal values of input parameters. The established modeling and optimization technique is generic and can be applied to any other experimental study. Several heavy metals such as Lead(II), Nickel(II), Manganese(II), Cadmium(II), Chromium(VI), and so on in the ash pond water contaminate the groundwater through leaching. In the present study, phycoremediation technique has been used to remove the heavy metals from simulated ash pond water. Artificial neural network (ANN) has been used to model the phycoremediation process, and hybrid artificial neural network‐simulated annealing (ANN‐SA) optimization technique has been used to optimize the process parameters and maximize the metal removal and biomass production. [ABSTRACT FROM AUTHOR]

Soil amendment with biochar is evaluated globally as a means to improve soil fertility, restoration of the ecological functions for anthropogenically polluted soils and also is a potential candidate to mitigate climate change. Application of biochar, a carbon-rich material developed from the combustion of biomass under no or limited oxygen supply has been found to ameliorate some of the negative effects of soil. Biochar modifications can lead to an increase in the water holding capacity as well as pH modification may also be used as a soil amendment. There are various other physical, chemical, and biological properties of biochar that can impact soils. However, the effects of biochar on soil biota have received much less attention than its effects on soil chemical properties. This review highlights essentially the various methods of preparation of biochar from waste biomasses and its usage as a potential soil amendment agent with a special emphasis on the effect of biochar on soil microbiology. A well-accepted mechanism of the effect of biochar on soil microbe environment still needs more focus. Therefore, the current review will further help in understanding the feasibility, safety, and effectiveness of biochar utilization for improving the fertility of the soil. This paper presents a detailed review of the biochar utilization as soil amendment describing the various methods of biochar preparation, its modification, usage for soil improvement, etc. A constructive review of the impact of biochar on soil microbiology has also been presented in the paper. [ABSTRACT FROM AUTHOR]

The objective of this paper is to develop Pythagorean fuzzy (PF) multi‐objective optimization by ratio analysis (PF‐MOORA) plus full MULTIplicative form (PF‐MULTIMOORA) method for solving multicriteria decision making (MCDM) problems with completely unknown information of criteria weights. In the model formulation process, a new distance measure is defined to quantify the difference between PF sets by combining Hamming distance and Hausdorff metric. This distance measure is, subsequently, implemented in entropy weight model for determining unknown weights of criteria, and also in reference point approach for obtaining preference indices of alternatives. To overcome the deficiencies occurred in existing MULTIMOORA method, like multiple comparisons, circular reasoning, and so on, an aggregation‐based approach is recommended in the proposed PF‐MULTIMOORA. To demonstrate the feasibility and practicality of the proposed method, an example concerning strategy prioritization of a tiles manufacturing company is presented. In the strategy evaluation process, at first, the judgement values provided by the decision maker are expressed in linguistic terms, and then those are converted into PF numbers through a PF weighting scale. The sensitivity of the proposed model is validated by changing of weights of criteria which impact on the ranks of the strategies. To show robustness of the developed method, the result attained by applying PF‐MULTIMOORA is compared with existing techniques, not only in crisp and fuzzy quantitative strategic planning matrix context, but also using four other MCDM methods, namely, modified PF‐MOORA, as a particular case of the proposed PF‐MULTIMOORA technique, PF weighted sum, PF‐TOPSIS and PF‐VIKOR. [ABSTRACT FROM AUTHOR]

This study represents an integrated approach consisting of AHP (analytical hierarchy process) and TOPSIS (technique for order preference by similarity to ideal solution) in Pythagorean fuzzy environment to solve multicriteria decision-making (MCDM) problems with completely unknown weights of criteria. Pythagorean fuzzy numbers are used to capture uncertainties associated with decision makers' ambiguous judgment for the selection of transportation companies in an MCDM context which can also be considered as an important area of supply chain management. In the proposed approach, a new distance measure based on cross-evaluation of Pythagorean fuzzy sets is introduced to overcome the disadvantages of existing distance measures. Unlike existing MCDM approaches, in which either subjective or objective weights of criteria are used, in this method AHP is modified using Pythagorean fuzzy information to calculate subjective weights of criteria, as well as Pythagorean fuzzy entropy weight model is applied to compute objective weights of criteria. Finally, both the weights of criteria are simultaneously taken into consideration to obtain final ranking of the alternatives. To demonstrate the application potentiality of the proposed method, a numerical example is considered with Pythagorean fuzzy input in the context of selecting the best transportation company which is one of the most important parts of transportation management. Further, a comparative analysis is executed with other existing techniques to establish the efficacy of the proposed methodology. [ABSTRACT FROM AUTHOR]

The graph theory is being used for representation in networks and chemical atomic structures very frequently. However, these days, uncertainties are imposed on such networks. Isomorphism in generalized fuzzy graphs has been introduced here to capture the similarity of uncertainties in different networks. Homomorphism, weak isomorphism, co-weak isomorphism and nearly isomorphism are defined with examples. Also, an application of image visualization is described. [ABSTRACT FROM AUTHOR]

This paper presents an innovative method for solving Pythagorean fuzzy (PF) multicriteria group decision-making problems with completely unknown weight information about criteria using entropy weight model, linear programming (LP) and modified technique for ordering preference by similarity to ideal solution (TOPSIS). At first, a new distance measure for PF sets is defined considering their degree of hesitancy and based on weighted Hamming distance and Hausdorff metric. To handle the fuzziness in criteria weights, PF entropy weight model is used to find the initial weights of the criteria in PF format. Following the concept of TOPSIS, an LP model is constructed on the basis of the view point that the chosen alternative should have the smallest distance from the positive ideal solution and the largest distance from the negative ideal solution. Then, the LP model is utilized to find optimal weights of the criteria. Using the newly defined distance measure, entropy weight model and LP model, TOPSIS is extended in PF environments. The existing methods are able to find criteria weights in the form of crisp values only, whereas proposed method is able to obtain those weights in PF format. Thus, the proposed method can overcome the drawback in computing criteria weight for multicriteria group decision-making in PF environments and reduce the information loss significantly. Several numerical examples are considered and solved to validate the superiority of the proposed methodology. [ABSTRACT FROM AUTHOR]

Abstract Reworking defective items any in multi-stage production systems have become a common issue for production industries. Due to random defective rate of production, it may contain several imperfect items as wastes. The reduction of those wastes through reworking in each stage of a cycle or at the end of stage of a cycle by an identifying opportunity design technique. A design is developed for making such type multi-stage production system. For this, imperfect products may be reworked within each cycle while avoiding any shortages or reworked after end cycle with shortages in each cycle. The aim of the model is to diminish wastes by reworking strategy for minimizing the total cost. For this purpose, the proposed study develops a multi-stage production model for an optimum production batch policy with random production of imperfect products. Two-stage inspection is considered for detecting those faulty products and ensuring that there are no faulty items anymore. As it is a long-run production system, setup cost plays an important role, an attempt at setup cost reduction has been made to reduce it by a discrete investment for each stage along with a budget constraint. The Lagrangian method is employed to solve the model and the global minimum cost for optimal decision variables is obtained. Ten lemmas are established to obtain the global optimum solution. The model shows that a large investment to reduce the setup cost is better than a constant setup cost. It is found that the imperfect items should be reworked after the end cycle. There are eight numerical examples, eight special cases, a sensitivity analysis of the key parameters, and sixteen graphical representations to demonstrate the proposed model. [ABSTRACT FROM AUTHOR]

Abstract The phenomena of global warming have increased the frequency of natural disasters. These disasters generate thousands of tons of waste and cause loss of human lives, environmental damages, and economic losses every year. Currently, disaster response policies are reactive in nature to bring the community back to normal routine. However, increased resilience against future disasters can be achieved by working on long-term planning and setting goals for ecological, economic, and social sustainability in disaster response policies. Keeping in view the importance of the considered issue, this study proposes a large-scale disaster waste management supply chain model, considering economic aspect via total waste processing, environmental aspect by greenhouse gas emissions from disaster waste processing, and social aspect by job opportunities generated during waste processing. To demonstrate the applicability of the proposed supply chain model, numerical experiments are performed on a large-scale case problem. Results show that there is a strong trade-off among the dimensions of sustainability. If decision makers want to achieve higher satisfaction levels against environmental and social objectives, the operational cost of waste management will increase accordingly. Numerical studies obtain the results in accordance with the values of the confidence level of decision makers and coefficient of compensation decided by the managers which also provides the flexibility for the decision makers of developing countries to obtain preferred compromised solution in accordance with their own preferences for the dimensions of sustainability during disaster waste management operation. Highlights • Framework of large-scale disaster waste management consists of three operations: recycling, incineration, and landfilling. • A multi-objective disaster waste processing supply chain model considering economic, environment, and social aspects has been developed. • Fuzzy programming approach provides both unbalanced and balanced efficient solutions for disaster waste processing supply chain. • The research takes the advantage of using fuzzy possibilistic programming to tackle the imprecise nature of available information in a post-disaster environment. [ABSTRACT FROM AUTHOR]

To ensure all products as perfect, inspection is essential, even though it is not possible to inspect all products after producing them like some special type products as plastic joint for the water pipe. In this direction, this paper develops an inventory model with lot inspection policy. With the help of lot inspection, all products need not to be verified still the retailer can decide the quality of products during inspection. If retailer founds products as imperfect quality, the products are sent back to supplier. As it is lot inspection, mis-clarification errors (Type-I error and Type-II error) are introduced to model the problem. Two possible cases are discussed for sending back products as defective lots are immediately withdrawn from the system and send back to supplier with retailer’s payment and for second case, retailer sends defective products during receiving next lot from supplier with supplier’s investment, like in food industry or in hygiene product industry. The model is solved analytically and results indicate that optimal order size and sample size are intrinsically linked and maximize the total profit. Numerical examples, graphical representations, and sensitivity analysis are given to illustrate the model. The results suggest that sending defective products maintaining the first case is the more profitable than the second case. [ABSTRACT FROM AUTHOR]

The article makes an effort in consolidating the developments in the field of advanced gravity separation techniques for processing fine particles over the last few decades. The application potentials of various unit operations and the influence of process variables and feed characteristics on the process performance are identified. Fundamentals of advanced gravity separators are discussed from theoretical and applied perspectives. Comparative analyses of various related unit operations are incorporated including the advantages and short falls of different advanced gravity separation techniques. A general guideline is presented that will help designing new mineral processing flow sheets with better efficiency indices. [ABSTRACT FROM AUTHOR]

A supply chain with multiple buyers leads to a hike in demand and for satisfying them, a high standard production manufacturing system is required. A predetermined production rate in a supply chain model with economic production lot size is quite inappropriate for this type of situation as production rate can be changed in some cases to fulfill demand of customers. Rate of production has an impact in maintaining process quality. Manufacturing quality deteriorates with an increasing rate of production. In this context, this paper develops a single-vendor multi-buyer supply chain model with variable production rate and imperfect quality of products. The unit production cost is considered as a function of the production rate. Three different production functions are established to relate process quality and production rate. Due to huge demand by multi-buyer, the lead time demand is considered as random variable and it follows a normal distribution. The objective of this study is to analyze how the flexibility of the production rate affects the product quality as well as entire supply chain cost under a single-setup multiple-delivery policy. A classical optimization technique is employed to obtain the global optimum solution. An illustrative algorithm is established to obtain the numerical results. Numerical examples and graphical interpretations, and sensitivity analysis are given to illustrate the model. Numerical study proves that the variable production rate effects a lot on the total cost of supply chain model. [ABSTRACT FROM AUTHOR]

Graph theory includes two unavoidable graphs, namely Euler graphs and Hamiltonian graphs. In this study, generalized fuzzy Euler graphs (GFEGs) and generalized fuzzy Hamiltonian graphs (GFHGs) are defined to express uncertain system like routes, networks. Here, even degrees of all vertices of graphs do not assure that the graphs are GFEG. Similarly, other properties of crisp Euler graphs and crisp Hamiltonian graphs are tested. Two algorithms are prepared to find Eulerian circuit in GFEGs and Hamiltonian circuit in GFHGs. In modern life, planning of efficient routes is very important for business and industry purposes. An application on planning of routes is described. [ABSTRACT FROM AUTHOR]

A fuzzy graph is a representation tool for many real networks. But, due to some restriction on edges, fuzzy graphs are limited to represent for some networks. In this study, generalized fuzzy graphs and generalized directed fuzzy graphs are discussed to avoid such restrictions. A pipeline network is expressed as a generalized directed fuzzy graph. In the pipeline network, the generalized membership values of edges and vertices are determined by the capacity of the pipelines. Also, fuzzy r-cuts and fuzzy (r1, r2, ..., rn)-cuts in the generalized fuzzy graphs are defined. [ABSTRACT FROM AUTHOR]

Due to rapid population growth and industrialization, the demand for electrical energy and its consumption has reached a critical point where it is no longer sustainable or stable. Therefore, it is imperative to explore new and reliable energy generation alternatives considering technical and economic perspectives, regardless of whether the community is isolated or urbanized. The research introduces a mixed-integer non-linear programming model of an energy supply chain that combines the roles of a manufacturer and retailer within a dynamic solar energy framework. The study highlights the manufacturer's significant efforts to sustain itself in a competitive market and emphasizes the importance of government subsidies to support this approach. To meet the demands of a dynamic environment, a non-continuous demand function is utilized to generate and transmit energy at a highly sustainable level, promoting ecological balance. The model's validity is confirmed through experimental evaluation using two case studies. Furthermore, by increasing the demand by 50%, this study demonstrates the potential for economic growth, resulting in a 20% profit for the manufacturer in the retail sector. This research ensures improved energy efficiency and greener consumption practices and addresses the optimal distribution of renewable energy to minimize imbalances. Finally, it reveals a pathway to sustainable development that promotes technological advancements while minimizing costs, offering a cost-effective scenario for the foreseeable future. [ABSTRACT FROM AUTHOR]

Global warming due to excessive use of fossil fuels has driven researchers to focus on sustainable energy sources for the future. For clean production systems, biofuel is expanding the domain of renewable and sustainable energy supplies. An efficient and sustainable supply chain plays a pivotal role in ensuring this supply. In this research, crop residuals in different agricultural zones, transportation for shipment of residual biomass as well as biofuel, multiple biorefineries, and multiple market centers are considered. The expense of the resources, the yield of residual biomass in agricultural zones, and the demand of market centers are represented by fuzzy numbers as they are assumed to be uncertain. The carbon emissions cost at all stages of the supply chain was also incorporated into this model. This objective of this study is to develop a supply chain model that minimizes the total cost of a second generation biofuel supply chain and location-allocation for agricultural zones and biorefineries to meet the uncertain demand for market centers. Two numerical examples are analyzed, and the results proves that the cost of biofuel production in biorefineries contributed 52.16%, which is a major proportion of the total cost. In the entire supply chain, the transportation sector is the foremost source of carbon emissions in an environment with 88.50% of the total carbon emissions. The results confirms that the proposed model is viable for designing second generation biofuel supply chains under uncertainty. Significant managerial insights of this research are also described to better express the efficiency of the model. [ABSTRACT FROM AUTHOR]

In today's global market, supply chain players have to cooperate mutually for extra benefits, long lasting paybacks, and to control carbon emission for a clean environment. This study develops the three-echelon sustainable supply chain model in the context of multi-level trade credit and single-setup-multiple-delivery policy for mutual coordination in financial support and reducing carbon emissions. These joint effects will benefit the firms for interim financing as well as minimize carbon emission for a clean environment. This model quantifies the effects of the environmental regulations and trade credit period under the single-setup-multiple-delivery policy. The supplier produces semi-finished items and transports it to the manufacturer, the manufacturer transform these semi-finished items into final products. These finished products finally transported to multi-retailer. The shipments are permitted to proceed from the particular lot during production instead after completing the entire lot This strategy save the environment by minimizing carbon emission. Additionally, a multi-level trade credit policy is considered in this model for short-term investment. An algebraic approach is used to derive a closed form optimal result for the designed model. This non-derivative method provides the effective solution algorithm. The main contribution of this study is to minimize the sustainable supply chain cost of the system by jointly considering the multi-level delay-in-payment, variable carbon emission cost, and variable transportation cost under the single-setup-multi-delivery policy. The study presents an optimal solution for the individual scenario and also derived a comparison between them with a numerical example. The findings directed that implementation of multi-level trade credit under single setup-multiple-delivery improves the economic and environmental performance of three-echelon supply chain. Sensitivity analysis of the developed study is also illustrated to prove the real practice. [ABSTRACT FROM AUTHOR]

Flux decline due to membrane fouling by surfactant micelles is the major problem limiting the use of micellar enhanced ultrafiltration (MEUF) for the treatment of wastewater. Understanding of underlying mechanisms of membrane fouling, adsorption kinetics and adsorption isotherm are very important for the successful application of MEUF studies. In the present study, an unsteady state model considering sequential occurrence of complete pore blocking and gel layer formation was proposed for explaining flux decline behavior during rhamnolipid based MEUF for simultaneous removal of Cd +2 and p-cresol from aqueous solution under batch concentration mode. The model was developed based on the Hermia's complete pore blocking model and resistance-in-series model coupled with gel layer theory incorporating the effects of feed temperature, variation of viscosity and retentate concentration with time, and pressure dependent mass transfer coefficient. A good agreement between the experimental data and model predictions was demonstrated. The effects of operating conditions were found to have a significant effect on the flux decline behavior and onset of gel layer formation. The use of ultrafiltration membrane for the study of adsorption kinetics and adsorption isotherm was demonstrated. Kinetic studies disclosed that both Cd +2 and p-cresol adsorption was better described by the pseudo-second order model for both single and binary solution. The results of isotherm studies revealed that adsorption of both Cd +2 and p-cresol was spontaneous in nature and equilibrium data was best fitted by Langmuir model with the maximum adsorption capacity of RHL vesicles of 208.33 and 53.27 mg g −1 for Cd +2 and p-cresol, respectively at 299 K. The model parameters of membrane fouling, adsorption kinetics and adsorption isotherm evaluated in this study could be useful in designing and scale up of RHL based MEUF process. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this study was to analyze flux decline behavior during ultrafiltration (UF) of jamun (Syzygium cumini [L.]) seed extract using Harmia's model and Koltuniewicz's surface‐renewal model. The effects of different transmembrane pressure and stirrer speed on the membrane fouling, permeate flux, and permeate quality were studied. Analysis of the results revealed that UF of seed extract was controlled by a cake filtration mechanism. Phenolic compounds in UF clarified and nanofiltration concentrated extract were identified and quantified using high‐performance liquid chromatography. Storage stability of quality parameters (total phenolic content (TPC), total flavonoid content (TFC), color, and clarity) of jamun seed extract and nanofiltration concentrated extract were studied at 4, 27, and 37 °C for 30 days. A first‐order kinetic model was successfully used to evaluate the degradation of TPC and TFC during storage. Three models (Arrhenius, Eyring, and Ball) were shown to be suitable to describe the temperature dependence of the deterioration rate constant of TPC and TFC. Experimental results confirmed that membrane processing of jamun seed extract enhanced the storage stability of all the quality parameters tested. The estimated model parameters might be useful for design and scale‐up of the system and to identify the appropriate storage conditions for industrial processing. [ABSTRACT FROM AUTHOR]

Experimental studies were performed in a stirred cell for concentration of MF-pretreated extracts from jamun (Syzygium cumini L.) leaves using nanofiltration over a wide range of operating conditions. Performance of nanofiltration process was evaluated in terms of permeate flux, flux decline and extract quality (total polyphenol content, total flavonoid content and antioxidant activity). A total of ten phenolic compounds including six phenolic acids and four flavonoids were identified and quantified in jamun leaf extract using HPLC. A combined sequential model consisting of Hermia's complete pore blocking and cake layer formation based on resistance-in-series theory was considered to explain the flux decline behavior with time. The model calculations were shown to be in excellent agreement with experimental flux data (R² > 0.90; SD < 2.5%). Experimental results showed that the operating conditions had significant effect on the onset of cake layer formation. The pore blocking resistance was found to be comparable with membrane resistance, while cake layer resistance was 20-40% of membrane resistance. In addition, the permeate flux for MF-pretreated extract was always higher than that for the untreated extract. The present study with the estimated model parameters provided important understandings into the underlying mechanisms of membrane fouling phenomena during concentration of jamun leaf extract. [ABSTRACT FROM AUTHOR]

This paper presents a continuous review inventory model with backorders and lost sales with fuzzy demand and learning considerations. The imprecision in demand is characterized by triangular fuzzy numbers. The triangular fuzzy numbers, counts upon lead time, are used to construct fuzzy lead time demand. It is assumed that the imprecision captured by these fuzzy numbers reduce with time because of learning effect. This implies that the decision maker gathers information about the inventory system and builds up knowledge from the previous shipments. Learning process occurs in setting and estimating the fuzzy parameters to reduce errors and costs. Under these considerations, the proposed model offers a policy and a solution algorithm to calculate the number of orders and reorder level such that the total annual cost attains a minimum value. The results of the proposed model are compared with the continuous review inventory system with fuzzy demand with or without learning effect. It is shown that learning effect in fuzziness reduces the ambiguity associated with the decision making process. Finally, numerical examples are provided to illustrate the importance of using learning in fuzzy model. The convexity of the total cost function is also proved. [ABSTRACT FROM AUTHOR]

Treatment of wastewater containing heavy metal ions and phenolic compound is a growing challenge due to their coexistence in many industrial effluents. The present study was aimed at the investigation of simultaneous removal of Cd +2 and p-cresol from aqueous solution by micellar-enhanced ultrafiltration (MEUF) with rhamnolipid (RHL) as a biosurfactant. MEUF experiments were performed according to statistical design considering the factors of solution pH (6.5–8.5), concentration of RHL (50–650 mg/L), Cd +2 (30–70 mg/L) and p-cresol (50–150 mg/L) in a stirred cell using 10 kDa flat sheet polyethersulfone membrane. The process was optimized to obtain the best possible feed conditions by the simultaneous maximization of the rejection of both Cd +2 and p-cresol, using the response surface methodology. The maximum rejection coefficient of 98.8% and 25% for Cd +2 and p-cresol, respectively were obtained for following optimal conditions: RHL: 370 mg/L, Cd +2 :60 mg/L, p-cresol: 75 mg/L and pH 7.8. Dynamic light scattering measurement showed that small-sized rhamnolipid vesicles (10–50 nm) were formed more than 93% in presence of Cd +2 and p-cresol, in the experimental range of RHL concentration greater than its critical micelle concentration (CMC), which was found to be 50 mg/L determined by surface tension measurements. Under the optimal feed conditions, the effects of various hydrodynamic conditions such as transmembrane pressure, stirrer speed and feed temperature on permeate flux and rejection of both pollutants were studied. Also, the performance of MEUF process was assessed through estimation of the distribution coefficient, vesicle loading and vesicle binding constants for both Cd +2 and p-cresol. [ABSTRACT FROM AUTHOR]

Due to the rising consumer concern and business responsibilities towards the environment, a closed-loop supply chain with a green design is considered. Reverse logistics and return policies are receiving more attention due to increasing consumer concerns and corporate responsibility toward the environment. Hence, this article presents a sustainable supply chain model for waste reduction incorporating reverse logistics operations. A suitable return policy is discussed here for deteriorating items, incorporating an eco-design framework. Since carbon emissions are a major environmental issue, a penalty tax for polluting is introduced to reduce carbon emissions. This model considers the cost of carbon emissions due to transportation, storage, production, landfilling, building construction, power supply, and loading/unloading. Unlike previous studies, this study investigates and compares three optimization techniques based on cooperative and non-cooperative associations. The mathematical formulation has been provided with different lemmas, theorems, and algorithms. By investigating end-of-life policies, it is shown that reused products can result in more profits for a company. A product usually becomes useless and non-recoverable after four uses. However, the product's reusability can be increased by investing more in the design stage of the item. • We developed a reverse logistics model considering environmental issues. • The problem is formulated for both cooperative and non-cooperative games. • The logistics involve a single-setup, multiple delivery system with resales. • A numerical example and sensitivity analysis to illustrate the model are provided. [ABSTRACT FROM AUTHOR]

In a production–consumption system, sustainable supply chain management is responsible for controlling excessive waste. In this study, two parallel production and consumption supply chains are proposed for waste nullification. The circular economic concept of 3R (reduce, restore, and recycle) is incorporated in this study. After deterioration, the primary product in the first chain becomes the raw material for the secondary chain production system (second production facility). During the shipment of waste to the recycling industry, loss of waste occurs owing to damage or leakage from the waste containers. The leakage cost (maintenance cost) of the waste container is included in the restoration of waste. The novelty of this study is validated by the optimal values of the price discount and container leakage cost, which emphasize the two factors of a circular economy: reducing and restoring waste in successive steps. The joint cost function (mixed-integer nonlinear programming) of the two-supply chain is optimized using a classical approach. A single-setup-multiple-delivery policy for the shipment of the primary, waste, and secondary products reduces the joint costs. A comparison of the single-setup-multiple-delivery and single-setup-single-delivery policies is presented for cost optimization. A significant numerical result is derived for the validation of this concept: as the leakage cost increases from $5 per container to $10 per container, the supply chain's overall cost immediately decreases by approximately 90%. However, the problem becomes infeasible beyond this range, which also validates the extreme sensitivity of the restoration of waste for recycling, which optimizes the entire cost of the supply chain. Another significant factor in the primary chain that helps to reduce the generation of waste is the price discount policy. The sensitivity analysis graph indicates that it is also an extremely sensitive parameter for optimizing the entire supply chain. [Display omitted] • Circular economy concept: Redesign (Reuse), Restoration, Recycle. • Joint inventory model of waste nullification. • Price discount policy for waste reduction. • Leakage cost for waste restoration for recycling. • Single-setup-multi-delivery policy for cost minimization of the total supply chain. [ABSTRACT FROM AUTHOR]

Space and labor are the two internal resources within a warehouse or cross-dock center which seek attention. Meaningful efforts in optimizing these two resources can reduce the operational cost or time of the goods delivery. The timely allocation of resources to order picking not only reduces the makespan and operational time but can also evade delay. In decentralized settings, where all the information is not properly shared between the players of the supply chain, miscommunication results in delays in product delivery. In this study, efforts were made to determine the pallet quantity of different product types in an order quantify when there is a gap in information shared and, based on that, the allocation of material handling devices or pickers was conducted. Each handling device is bounded by a workload to eliminate the option of idle resources and ensure it is utilized properly. A mixed integer linear programming model was formulated for this study and was solved using Lingo. Numerical experiments were performed under varying resource numbers and pallet quantities to investigate the circumstances where the number of pallet types and allocation of machines have the highest benefit. The results confirm that a change in the pallet quantity of the products increases the total picking time. However, an increase in the number of handling devices minimizes the level of over-utilization of a particular machine. [ABSTRACT FROM AUTHOR]

The present consumer behavior is manipulated by "fast fashion", where purchasing new, trendy, affordable clothes is preferred over recycling old ones. This changing mannerism has escalated the GHG emissions from the fashion industry. Energy-intensive raw material production, preparation, and processing contribute to considerable emissions. The management of the returned goods from the primary market and further processing through the secondary outlets indulge in reverse logistics. In this paper, efforts are made to minimize the total cost and the carbon emission amount during the process of managing the return articles from the primary market to the reverse distribution center, further processing of the articles at the secondary outlet, and the return of the unsold or excess articles from the secondary outlet. Reverse cross-docking has been implemented in managing the return articles, while environmental concerns over GHG emissions have been addressed by investing in green technology under a strict carbon cap policy. In this research, return articles from the primary and secondary markets, rework of the returned articles, and disposal of the impaired returned articles have been considered. The carbon emission cost at all stages of transportation, rework, or disposal has also been incorporated into this model. A constrained mixed integer linear programming model is proposed and solved considering green investment. A numerical example has been formulated to investigate the effect of green technology on the total cost. The results portray that, though the total cost increases by nearly 2% due to investment in green technology, it ensures a considerable drop of 23% in the carbon emission amount. Also, the result is successful in establishing that reverse cross-docking is a better option than traditional warehousing in terms of minimizing the cost. [ABSTRACT FROM AUTHOR]

The adsorption of amphiphilic molecules of varying size on solid-liquid interfaces modulates the properties of colloidal systems. Nonionic, poly(ethylene oxide) (PEO)-based amphiphilic molecules are particularly useful because of their graded hydrophobic-hydrophilic nature, which allows for adsorption on a wide array of solid surfaces. Their adsorption also results in other useful properties, such as responsiveness to external stimuli and solubilization of hydrophobic compounds. This review focuses on the adsorption properties of PEO-based amphiphiles, beginning with a discussion of fundamental concepts pertaining to the adsorption of macromolecules on solid-liquid interfaces, and more specifically the adsorption of PEO homopolymers. The main portion of the review highlights studies on factors affecting the adsorption and surface self-assembly of PEO-PPO-PEO block copolymers, where PPO is poly(propylene oxide). Block copolymers of this type are commercially available and of interest in several fields, due to their low toxicity and compatibility in aqueous systems. Examples of applications relevant to the interfacial behavior of PEO-PPO-PEO block copolymers are paints and coatings, detergents, filtration, and drug delivery. The methods discussed herein for manipulating the adsorption properties of PEO-PPO-PEO are emphasized for their ability to shed light on molecular interactions at interfaces. Knowledge of these interactions guides the formulation of novel materials with useful mesoscale organization and micro- and macrophase properties. [ABSTRACT FROM AUTHOR]

This model extends a two-echelon supply chain model by considering the trade-credit policy, transportations discount to make a coordination mechanism between transportation discounts, trade-credit financing, number of shipments, quality improvement of products, and reduced setup cost in such a way that the total cost of the whole system can be reduced, where the supplier offers trade-credit-period to the buyer. For buyer, the backorder rate is considered as variable. There are two investments to reduce setup cost and to improve quality of products. The model assumes lead time-dependent backorder rate, where the lead time is stochastic in nature. By using the trade-credit policy, the model gives how the credit-period would be determined to achieve the win-win outcome. An iterative algorithm is designed to obtain the global optimum results. Numerical example and sensitivity analysis are given to illustrate the model. [ABSTRACT FROM AUTHOR]

To maintain a multi-stage cleaner production process, the major task is eliminating all defective items during the production system and an investment is necessary to reduce the probability of in-control state to out-of-control state of machinery system. In this direction, a logarithmic expression suggested by Porteus (1986) to consider in a single-stage imperfect manufacturing process for quality improvement, whereas this paper enables to consider the similar investment in a complex multi-stage imperfect manufacturing process to clean the production system. Using it, this paper develops a joint replenishment problem for complex multi-stage quality improvement. The study investigates a stochastic inventory model with a budget constraint for simultaneously optimizing number of shipments, replenishment interval, safety factor, backorder discounts, quality factor, and lead time as decision variables. Lead time is assumed as stochastic in nature, where a lead time crashing cost is used to reduce the lead time. As lead time is stochastic, a backorder price discount is allowed to save lost sells. To solve this problem, an improved algorithm is developed and two theorems are proved to obtain global optimal solution for this model analytically. Finally, some numerical examples and graphical illustrations are given to illustrate this model. [ABSTRACT FROM AUTHOR]

In this study, aqueous extraction of phenolic compounds from jamun (Syzygium cuminiL.) seed was undertaken. The effects of various parameters such as extraction temperature (34.8–85.2°C), extraction time (49.8–100.2 min), and liquid-to-solid ratio (9.8–60.2 mL/g) on the extraction yield, extract purity (i.e., total polyphenol content), and its antioxidant activities (1,1-diphenyl-2-picrlthydrazyl free radical scavenging assay and ferric reducing antioxidant power) were investigated. Response surface methodology was used to optimize the extraction conditions. The optimum extraction conditions (49.2°C, 89.4 min, and 51.6:1 mL/g) produced an extract with 17.3% extraction yield, high total polyphenol content (415 mg gallic acid equivalent/g dried extract) and significant antioxidant activity (IC50: 35.4 ± 0.7 µg/mL). The high-performance liquid chromatography analysis of seed extract revealed the presence of gallic acid (90.8 mg/g dried extract), ellagic acid (36 mg/g dried extract), caffeic acid (26.07 mg/g dried extract),p-coumaric acid (0.26 mg/g dried extract), catechin (9.05 mg/g dried extract), epicatechin (0.42 mg/g dried extract), and quercetin (1.54 mg/g dried extract). Tannic acid (188.5 mg/g dried extract) was also identified as a major phenolic compound. The extraction kinetics was also studied and experimental data were fitted to four kinetic models such as first-order model, second-order model, Peleg’s model, and Minchev and Minkov model, to evaluate their applicability. [ABSTRACT FROM AUTHOR]

Optimal batch size reduces variability in the lean manufacturing process with minimized system costs. It simplifies the scheduling, enhances the quality, reduces inventories, and improves the production process continuously. On account of this, determining optimal batch size is the area of interest for the researchers with the objective of reducing inventories and related system costs. Products of the textile sector are produced generally in a multi-stage production setup, and it consists of random defective rate within the long-run production systems. In this context, this paper revisits an economic production quantity (EPQ) model with an imperfect multi-stage production system and analyzes an inventory model by considering a random defective rate in a cleaner multi-stage lean manufacturing system. These defective items are reworked and converted into perfect quality items by incurring additional processing costs. The proportion of defective items can be reduced through continuous improvements in the production process reliability by performing various lean manufacturing techniques, enlisting the total productive maintenance at the highest rank. A mathematical model is developed using a familiar beta distribution density function for the random defective rate. Then, the total cost of the system is minimized through analytical technique, where the batch size is a decision variable. Outcomes through analytical and numerical study confirm that optimum batch size is obtained by this model and it has a direct relationship with number of production stages. [ABSTRACT FROM AUTHOR]

Fuzzy graphs are the backbone of many real systems like networks, image, scheduling, etc. But, due to some restriction on edges, fuzzy graphs are limited to represent for some systems. Generalized fuzzy graphs are appropriate to avoid such restrictions. In this study generalized fuzzy graphs are introduced. In this study, matrix representation of generalized fuzzy graphs is described. Completeness and regularity are two important parameters of graph theory. Here, regular and complete generalized fuzzy graphs are introduced. Some properties of them are discussed. After that, effective regular graphs are exemplified. [ABSTRACT FROM AUTHOR]

Several industries controls carbon emission during transporting products due to increased transportation for obtaining the best transportation way with reduced cost. This study considers a three-echelon supply chain model where the supplier makes semi-finished products and transports to manufacturer for finished products. The manufacturer transports products by single-setup-multi-delivery policy to multi-retailer. The aim of the model is to reduce the supply chain cost by considering variable transportation and carbon emission costs are considered due to several shipments. An algebraic approach is employed to obtain the closed-form solution. Numerical example, sensitivity analysis, and graphical representations are given to illustrate the model. [ABSTRACT FROM AUTHOR]

Environmental protection and the availability of natural resources help to maintain sustainability for manufacturing system. Reusing/remanufacturing economically viable used products, collected from end customers, has become an integral part of many supply chain operations. Remanufacturing with green investment plays an essential role in sustainable supply chain management by utilizing an environment-friendly approach. Considering this environmental, social, and economic development of society, this model mainly focuses on the flexibility of production rate under the multi-retailer based supply chain to satisfy customer's demand. In this study, the manufacturer produces final products from new raw materials and used collected products. Subsequently, the products are transported to retailers and sold along with their service facilities. A mathematical model of this flexible manufacturing–remanufacturing system is developed to improve the service and to maintain sustainability always. The global optimization is established theoretically and a proposition is developed. Through numerical experiments, the global optimality is also verified. Some special cases, along with a comparison graph, are also provided for the validation of this results. The obtained results indicate that the concerned idea of service facility helps the customer to choose products without hesitation and the supply chain management achieves the maximum profit under green investment. It is found that the proposed study converges over the fixed production rate and without service studies. • We propose a sustainable supply chain model under environment friendly approach. • Multi-retailer based SCM is developed with a flexible production and a variable demand. • Service facility under manufacturing–remanufacturing maximizes the SCM total profit. • Separate holding costs for fresh and recovered items are helpful for smooth business. • The SCM is developed through a green investment and a waste reduction initiative. [ABSTRACT FROM AUTHOR]

The aim of the present study was to investigate the potentiality of an integrated membrane process for the purification and the concentration of phenolic compounds from aqueous jamun (Syzygium cumini L.) seed extract. The aqueous seed extract obtained at optimal condition (temperature: 49.2 °C, time: 89.4min, and liquid to solid ratio: 51.6:1 mL/g) was submitted to cross flow ultrafiltration for initial clarification, followed by concentration using nanofiltration under batch concentration mode. A detailed parametric study was carried out to investigate the effect of various process parameters such as transmembrane pressure, cross-flow velocity (or stirrer speed) on the permeate flux and permeate quality. Using classical film theory, a steady state gel polarization model incorporating the effect of transmembrane pressure difference and viscosity variation was proposed for the prediction of permeate flux during cross flow ultrafiltration of aqueous seed extract. The predicted flux values were successfully compared with the experimental results. Experimental results showed that the operating conditions had significant effect on permeate flux, recovery of polyphenols, purity and antioxidant activity of phenolic extract. Ultrafiltration experiments at lower operating pressures (276 and 414 kPa) using 100 kDa membrane resulted in the recovery of 59-66.7% of total polyphenol content in the clarified extract with the purity of 49-58.3% starting from an extract purity of 39.2%. The clarified extract could be successfully concentrated about three times higher using 250 Da nanofiltration membrane at volume concentration ratio of three. The present study revealed that the UF/NF integrated membranes process was successful in clarifying and concentrating phenolic extract obtained from jamun seed with enhanced purity and antioxidant activity. [ABSTRACT FROM AUTHOR]

This paper illustrates a channel coordination and quantity discounts between a vendor and a buyer with single-setup multi-delivery (SSMD) strategy to reduce the joint total cost among supply chain players. The benefit of the coordination between a buyer and a vendor is considered as the vendor requests to the buyer for changing the ordering quantity such that the vendor can be benefited from lower inventory costs. After accepting the buyer’s condition, the vendor compensates the buyer for his increased inventory cost and gives consent for additional savings by offering a quantity discount. The centralized decision making is examined for the effect of this strategy with the presence of backorder for buyer and inspection cost for the vendor. The quantity discount strategy, with the presence of variable backorder and inspections, can allow more savings for all players of supply chain. Some numerical examples, sensitivity analysis, and graphical representations are given to illustrate more savings from existing literature and comparisons between the several demand values. [ABSTRACT FROM AUTHOR]

Electric field-enhanced cross-flow ultrafiltration of enzyme-treated apple juice is studied in a rectangular cell using a 30 kDa molecular weight cut-off flat sheet polyethersulfone membrane under turbulent flow conditions for various operating conditions. Application of direct current (DC) electric field has resulted in a significant augmentation of permeate flux. Using classical film theory, a steadystate gel polarization model incorporating the effect of electric field and pressuredependent mass transfer coefficient is proposed for the prediction of permeate flux. From the steady-state model, gel layer concentration, effective diffusivity and effective viscosity of gel-forming solute in apple juice are estimated. A gel layer model based on resistance-in-series theory is proposed and numerically solved to quantify the transient flux decline and development of gel layer thickness over the membrane surface. The model predictions are successfully compared with the experimental results. [ABSTRACT FROM AUTHOR]

Monte Carlo localization is a powerful and popular approach in mobile robot localization. Line segment-based maps provide a compact and scalable representation of indoor environments for mobile robot navigation. But Monte Carlo localization has seldom been studied in the context of line segment-based maps. A key step of the approach–and one that can endow it with or rob it of the attributes of accuracy, robustness and efficiency–is the computation of the so called importance weight associated with each particle. In this paper, we propose a new method for the computation of importance weights on maps represented with line segments, and extensively study its performance in pose tracking. We also compare our method with three other methods reported in the literature and present the results and insights thus gathered. The comparative study, conducted using both simulated and real data, on maps built from real data available in the public domain clearly establish that the proposed method is more accurate, robust and efficient than the other methods. [ABSTRACT FROM AUTHOR]

Due to heavy transportation for single-setup multidelivery (SSMD) policy in supply chain management, this model assumes carbon emission cost to obtain a realistic behavior for world environment. The transportation for buyer and vendor is considered along with setup cost reduction by using an investment function. It is assumed that the shipment lot size of each delivery is unequal and variable. The buyer inspects all received products and returns defective items to vendor for reworking process. Because of this policy, end customers will only obtain nondefective items. The analytical optimization is considered to obtain the optimum solution of the model. The main goal of this paper is to reduce the total cost by considering carbon emission during the transportation. A numerical example, graphical representation, and sensitivity analysis are given to illustrate the model. [ABSTRACT FROM AUTHOR]

Electric field-enhanced separation of polyethylene glycol (PEG) from an aqueous electrolyte solution of bovine serum albumin has been carried out. Experimental results show significant improvements in both the permeate flux and the PEG transmission with the application of a suitable d.c. electric field. A mass transfer model based on film theory is proposed for prediction of permeate flux and observed retention of PEG. The model uses a single parameter, namely real retention (Rr2) of the PEG which is evaluated by optimizing the experimental values of steady state permeate flux and the permeate concentration. Model predictions are in good agreement with the experimental data. [ABSTRACT FROM PUBLISHER]

The purpose of this study is two-fold. The first is to consider supplier's and retailer's trade-credit policy for fixed lifetime products and the second is to extend Mahata's model with time varying deterioration where Mahata (Expert Syst Appl 39(3):3537-3550, ) wrote exponential deterioration but actually he considered constant deterioration. We assume that the suppliers offer full trade-credit to retailers but retailers offer partial trade-credit to their customers. Some numerical examples along with graphical representations are given to illustrate the model. [ABSTRACT FROM AUTHOR]

In the present work, ultrafiltration of enzyme pre-treated apple juice is studied under batch concentration mode in a stirred batch cell. Response surface methodology (RSM) is used to study the effects of incubation temperature, incubation time and enzyme concentration and their mutual interaction effects on the physical characteristics of apple juice such as alcohol insoluble solid (AIS), viscosity, clarity, total polyphenol, flavonoid and protein during enzyme treatment of apple juice. A central composite design (CCD) is employed to develop the quadratic model and optimizing the operating conditions of the enzyme treatment process for obtaining the desired characteristics of juice. During ultrafiltration enzyme pre-treated apple juice, the flux decline behavior is modeled using Hermia's approach for constant pressure dead-end filtration laws. Two model parameters, namely intermediate pore blocking coefficient and cake filtration coefficient are obtained by minimizing the error involved between calculated and experimental flux data. These parameters along with known operating conditions, membrane permeability and physical properties of feed enable one to predict the transient permeate flux decline. The effect of various operating conditions, such as feed temperature, stirrer speed and transmembrane pressure on the flux decline is demonstrated. Experimental results show that operating conditions have significant effect on the onset of cake formation as well as on the flux decline behavior. The model predictions are in good agreement with the experimental data. [ABSTRACT FROM AUTHOR]

The ability to manipulate polymer adsorption is useful for applications involving colloidal stabilization, for example, paints, cosmetics, lubricants, and mineral and waste-water treatment. We have an ongoing interest on the use of organic molecules for modulating the aqueous solution and adsorption properties of poly(ethylene oxide)–poly(propylene oxide)–poly(ethylene oxide) (PEO–PPO–PEO) block copolymers. In the present study, the influence of low molecular weight PEO homopolymer on the adsorption of a representative PEO–PPO–PEO block copolymer (Pluronic P105: EO37-PO56-EO37) at the surface of protonated silica nanoparticles dispersed in water is investigated. Pluronic P105 forms hydrophobic domains on the surface of protonated silica at a critical surface micelle concentration, csmc, of 0.02 wt% in the presence of 0.1 wt% silica nanoparticles in water, well below the cmc of Pluronic P105 in water (0.6 wt%). Dye solubilization experiments reveal an increase in the PEO–PPO–PEO block copolymer csmc with increasing amounts of added PEO homopolymer. The resulting critical displacer concentration for PEO homopolymer of molecular weights 200 and 600 Da was measured to be 0.1 wt% and 0.07 wt%, respectively, in the presence of 0.1 wt% silica nanoparticles. Capillary viscometry measurements indicate a decrease in the adsorbed layer thickness at the protonated silica surface with increasing PEO homopolymer concentration. The data presented herein are consistent with a physical model which considers “patches” of PEO–PPO–PEO block copolymer and PEO homopolymer adsorbed at the silica surface. [ABSTRACT FROM AUTHOR]