Search

Background: This study aimed to model optimization of strategic environmental management decisions in the operation of reverse osmosis desalination, emphasizing the costs required for the environmental protection during the production of freshwater using reverse osmosis technology. Methods:This analytical research was conducted in five cities of Hormozgan province in Iran for 18 months from February 2018 to September 2019. The research includes eight phases of defining the research problem, data collection, preliminary data analysis and decision criteria, mathematical modeling, model validation, information preparation, analysis and finally discussion, conclusions and suggestions. The main environmental issues were the carbon dioxide (CO2) release rate due to power demand and rejected brine water (RBW) were entered the mathematical model.Results:The desalination plants of Abu Musa, Bandar Abbas, Qeshm, Sirik, and Hormoz with water production flow rate of 2100, 89 000, 5300, 3300 and 1500 m3/d can generate 2360.82, 100053.80, 5958.260, 3709.86 and 1686.30 tons/year of CO2 emissions respectively. This output requires 1.35, 57.47, 3.42, 2.13 and 0.97 million USD for controlling the process, respectively. For reduction of the negative effect of RBW 0.75, 22.79, 1.78, 1.15 and 0.55 million USD respectively, is needed.Conclusion: Recommendations for environmental impacts protection of RBW, for desalination capacity up to 50 000 m3/d, are; (a) for desalination capacity up to 50 000 m3/d; dilution the RBW using raw water before entering into the sea, (b) for capacity of 50 000-100 000 m3/d; dispersing RBW in sea using diffuser, and (c) for capacity more than 100 000 m3/d; hybrid water desalination plants and power plant. Application of power plant cooling water to dilute RBW may reduce cost.

Human resource management (HRM) in public organizations managed based on a balanced scorecard requires a different narrative on the map of strategic goals than in private organizations. However, this issue is not widely recognized and discussed. This study aims to identify strategic goals and outline an HRM strategy with a stakeholder approach from a corporate culture perspective based on a balanced scorecard by examining and highlighting areas that should be included in the revised narrative. This exploration was carried out through qualitative research, particularly a thematic analysis based on data from the Kish Free Zone Organization. Therefore, using the themes obtained, a human resources strategy map was presented based on a balanced scorecard. The six-step Clarke-Braun process and the three-step Attride-Stirling thematic classification method were combined into a thematic network, and a seven-step research process was created. Data was collected through interviews with stakeholders in the Human Resources (HR) unit. These stakeholders are (1) HR employees (2) employees of other entities (3) senior and middle management (4) family of employees (5) HR department of related companies (6) retirees, and (7) customers of this entity. To identify strategic goals and a human resource strategy map, 187 main topics, 39 organizational topics, and 12 global themes were identified after transcription of the interviews, including (1) the development of family policies (2) promoting the well-being, health, and well-being of employees (3) improving productivity HR department (4) promoting the human dignity of the staff (5) developing an organizational culture based on customer orientation and innovation (6) empowering employees (7) development HR information system (8) strategic recruitment and retention of employees (9) performance management and development employees (10) strategic transformation of HRM based on research and process reform (11) adjusting the allocation and use of the HR budget to the organization's strategy and (12) improving the accounting mechanism for the personnel budget. This study is innovative due to the proposed approach to redesign the strategy map and the balanced scorecard from a human resource management perspective, methodically, due to adopting a combined thematic analysis process and constructing related narratives and stakeholder approaches from a corporate culture perspective.

Companies employ several forms of cooperation to reach success in the global competitive market. Coordination models seek to find the practical solution to encourage supply chain members to make decisions to improve overall profit. Note that, cooperation contracts are useful tools to make supply chain members behave coherently and coordinately with each other in order to gain SC's profit as final purpose. This paper aims to determine the most appropriate contract that can make cooperation between SC levels. In this case supply chains and cooperation contracts were reviewed and as a result of this study. Afterwards, a two echelons SC and mentioned contracts in the title chose are investigated. By considering the game theory approach, static games by complete information and Nash equilibrium as a solving method and probabilistic demand of consumers, initial profit function models of SC echelons were designed and subsequently, the secondary models redesigned with the consideration of the specific circumstances of each contract. Then, some experiments were designed by MINITAB software and solved by EXCEL and LINGO software. Eventually, by analyzing outputs, rebate contract is determined as the most appropriate way of establishing cooperation among the SC levels.

One of the essential factors of project success is selecting the proper delivery method. This study aimed to provide a new hybrid decision-making framework to assist project stakeholders in evaluating and selecting the most appropriate Project Delivery System (PDS) and documenting the decision process. For this purpose, the selection factors of PDSs were obtained from a literature review, and critical selection factors were screened based on the fuzzy Delphi method, whereby expert feedback was on Information and Communication Technology (ICT) projects was obtained. Subsequently, the ICT project risks were identified and categorized into six competitive constraints, including time, cost, quality, reputation, value, and scope, and the risk factors were prioritized in each area. Then, the effect of project risks on the decision criteria was investigated using a fuzzy cognitive map (FCM). Finally, the PDSs were ranked through Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). This article researched a novel multi-layer decision system combining the FCM and FTOPSIS techniques. The decision criteria received their weights from the evaluation of the causal relationships between PDS selection factors and project risks. Thus, PDSs were ranked based on different project characteristics, the opinions of stakeholders, and the effect of project risks on the decision-making process; this increased the likelihood of project success. The results showed that the impact of the most critical project risks on the selection factors was so severe that they changed the weight of the criteria in the decision matrix and, subsequently, changed the ranking of decision options.

The project management is planning and conducting projects within time, cost and quality is determined towards the creation of specific results. The aim of this research was to develop mathematical models for the trade off time, cost, quality and risk of the project which parameters of its activities have been estimated randomly with grey numbers. In the projects, managers are looking for the optimal combination of time, cost and quality of the project and considering the risk, while information is limited and insufficient in this area. Using the proposed method with grey numbers can help to manage projects well in these conditions. For solving the model / methodology, the hybrid of fuzzy goal programming and grey linear planning has been predicted. By examining the responses, it seems that there is a possibility for them to be improved with goal programming; therefore, the further stages with goal programming for better satisfactory answers were presented to the project manager. For a case study, the project(s) in Iran Khodro Company is selected.

To cooperate or not is one of the most challenging issues of supply chain management era. If the supply chain is managed optimally, the entire profitability increases. Meanwhile, corporate Social Responsibility (hereafter CSR) is defined as the social and ethical behavior of supply chain members against stakeholders such as shareholders, final customers, employees and executives. Moreover, the observance of the social responsibility obligations is of great importance for consumers and shareholders of companies. The decisions of the supply chain’s members play a direct role in determining the profits of each. These decisions are in conflict with other members in a competitive environment. In this paper, the contradictory variables encompasses the cost resulting from the performance of corporate social responsibility, inventory, shortage, advertising and pricing in a two-level supply chain, consisting a manufacturer and a retailer. After identifying the quantitative variables for measuring the social responsibility using Delphi-Fuzzy methods and Interpretive Structural Modeling, the most important and influential variable of measuring the social responsibility performance (forced labor ratio) has been selected. Subsequently, after modeling the profit function of each player, optimal results were emanated according to the bargaining power of each member and based on Nash and Stackelberg games. Afterwards, with numerical examples, the optimization and sensitivity analysis of social responsibility in each model has been discussed. The results indicate that the profit of manufacturer and retailer reduces by increasing the proportion of forced labor. Based upon Nash equilibrium, the manufacturer’s profit decreases with a slight slope; nonetheless, on retailer and manufacturer leadership models, the profit decreases with a slight increase of the forced labor.

In the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.

Prominent influence of transportation costs on supply chain overall profit indicates the importance and emergence of transportation optimization models. Regarding this issue and in view of realistic situation consisting of non-deterministic information, in this research optimizing inbound and outbound transportation costs of a multi echelon supply chain has been considered. To deal with uncertain time deliveries and pricing strategies adopted by different members of supply chain, in conjunction with unpredictable demand rate, fuzzy logic and specifically Trapezoidal Fuzzy Numbers (TrFNs) are included. After designing a fuzzy binary multi objective model based upon structural assumptions, the solving approach is proposed and the model is employed on Iranian steel supply network to illustrate the potential and advantages of our scheduled model. The bi-objective mixed integer fuzzy programming model presents and encompasses many realistic circumstances making the model applicable in network transportation cases.

Multi criteria decision aid (MCDA) deals with the problem of evaluating a set of finite alternatives regard to a set of finite criteria. A remarkable volume of qualitative and quantitative researches are done on decision making methods and situations, indicating its important role for managers at different organizational levels. These types of problems are applied in many different fields of human life. A challenging feature of these problems is non-existence of an optimal solution due to considering multiple criteria and the proposed methods seeking to find a satisfactory solution called efficient of Pareto-optimal. In consideration of MCDA problem, in this paper a new method is proposed for solving DM problems, consisting three fundamental steps of initialization, orthogonalization, and comparison. Thus, a new MCDA method called total area based on orthogonal vectors (TAOV) is introduced. This method is constructed on orthogonality of decision criteria. Application of TAOV method is illustrated in a decision problem and its performance is evaluated regard to other MCDA methods. Furthermore, its features are explained around the features of a desirable MCDA method. The obtained results indicate that the TAOV method can be considered as an acceptable method of handling multi-criteria decision making problems.

Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.

The role and importance of supply chain management, has faced with many challenges and problems. Although a comprehensive model of supply chain issues, has not been explained, we have to indicate that issues such as reviewing the theoretical foundations of information systems, marketing, financial management, logistical and organizational relations have been considered by many researchers. The objective of supply chain management is to improve various activities and components to increase overall supply chain system benefits. In order to achieve the overall objectives, many contradictions may occur between the components and different levels of supply chain and the contradictions that these disorders over time, result in decreased strength and competitiveness of the supply chain. Such conflicts, like marketing costs (advertising), pricing and inventory can occur during the supply chain life cycle. A Game Theory approach with respect to property is the appropriate tool for collaboration in the supply chain. This tool is used for collaborative making in any kind of supply chain such as cooperative supply chain and non-cooperative supply chain. In the present study and assuming a lack of cooperation between different levels of a supply chain, a dynamic game with complete information has been generated. In addition identifying appropriate leaders of various levels of the supply chain is considered. Non-Cooperative dynamic game mode (Stackelberg Game), for each of the three levels of supply chain including retailers, suppliers and manufacturers are modeled. Depending on the bargaining power and its position in the market, any level of supply chain can make a leader of the following rule. In the present study, the equilibrium model to play Stackelberg game may be led by a leader or leading players and ultimately identifying and modeling the appropriate unlimited three level supply chain are determined.

Determining the optimal policy of inventory have been always one of the main challenges in inventory management area in which several research have been conducted to address this issue. A vast majority of proposed approaches are very simple models to the extent that they simplify the real-world conditions and fail to consider the real uncertainties. To determine the optimal inventory policy of supply chains, on the other hand, there exist many influential uncertainties. In this thesis, an integrative probabilistic model is developed to model the uncertainty of the optimal inventory policy of multi-echolon supply chains using Bayesian networks (BNs) a state-of-the-art technology in modeling uncertainty. BNs provide a framework for presenting cause and effect relationships and enable probabilistic inference among a set of variables. The new approach explicitly quantifies uncertainty in qualitative and quantitative uncertain variables in customer, retailer, manufacturure, and supplier levels and provides an appropriate method for modeling complex relationships for process capability analysis, such as common causal factors, formal use of experts' judgments, and learning from data to update previous beliefs and probabilities. The capabilities of the proposed approach are emplemented in Agenarisk software by a real case study.

Data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homogenous decision making units. This methodology is applied widely in different contexts. Regarding to its logic, DEA allows each DMU to take its optimal weight in comparison with other DMUs while a similar condition is considered for other units. This feature is a bilabial characteristic which optimizes the performance of units in one hand. This flexibility on the other hand threats the comparability of different units because different weighting schemes are used for different DMUs. This paper proposes a unified model for determination of a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights that rank the DMUs and increase the model's discrimination power. Comparison of the proposed method with some of the previously presented models has shown its advantages as a DMUs ranking model.

The development of Multiple Criteria Decision Making Techniques is to provide the possibility of using multiple criteria in decision making problems. Multi-criteria decision making problems primarily relate to choosing the best option among several available options and according to some indicators. One of the major issues in this regard is to determine the importance weights of decision criteria. Various methods such as Entropy, LINMAP and Saaty’s method have been presented for determining the weights of the indicators. In this paper, a non-linear model based on the logic of TOPSIS method is proposed to estimate the ideal weights. Simplicity, ‌ Reduction of received data from the decision makers in the evaluation process, and the possibility of considering his comments about the preference of indicators to each other can be cited as the advantages of this method

By considering the role and importance of supply chain management, this concept faced with many challenges and problems. Although there is no explanation of a comprehensive model for supply chain issues, a review of theoretical issues in this field, indicates that information systems, marketing, financial management, logistical and organizational relations, matters of interest to researchers in this field. The objective of supply chain management is improvement of various activities and components of a supply chain to increase overall supply chain system. Many contradictions between the components and different levels in order to achieve the overall objectives of the supply chain have been observed, and these disorders may result by decreased strength and competitiveness of supply chain. The main contradictions that are considered in this paper are related to inventory, pricing and also marketing costs in an unlimited three echelon supply chain. The basics of game theory make it a suitable and reliable tool for solving contradiction situations by considering all levels and players goal. In this paper, finding equilibrium of inventory, pricing and marketing cost of an unlimited three echelon supply chain(SC), consisting of supplier, manufacturer and retailer is considered. K retailer, M manufacturer and S supplier are acting, and different leadership of each level are examined to find the highest payoff for the supply chain.

The Customs Tariff is based on the World Customs Organization's (WCO) Harmonized Commodity Description and Coding System (HS) and its impact of industry competitiveness is known for everyone. In this paper, by considering IRAN I.R. industries,the impact of change in custom tariff on domestic industries have been analyzed. Many models have been used to analys and evaluate the effect of change in custom tariff on domestic industries. In this paper System Dynamics(SD) approach and modeling has been used to describe this problem. By using Casual Loops(CL) and also Stock And Flow diagram(CFD), the model of problem has achived. At next step, depending on the type of variables(State variable, Rate variable, Auxiliary variable, parameters, …) the relation of variables are identified and the model is completed. At final step the model was sumilated and run by VENSIM software and the results were outcomed. This paper declares that decreasing the custom tariff will improve domestic industries competitiveness in long terms by developing the infrastructure of domestic industry for gaining more market share

In recent years, there are several methods introduced for the improvement of operational performances. Total quality management and supply chain management are two methods recommended for this purpose. These two approaches have been studied in most researches separately, while they have objectives in common, and this makes them a strategic means, which can be used, simultaneously. Total quality management and supply chain management play significant roles to increase the organizational competitiveness power. Moreover, they have only one purpose that is customer satisfaction, and they are different only on their approaches to reach their objectives. In this research, we aim to study both approaches of quality management and supply chain, their positive increasing effects that may be generated after their integration. For this purpose, the concept and definitions of each approach is studied, independently, their similarities and differences are recognized, and finally, the advantages of their integration are introduced.

By the new developments occurring in technology, management theories, manufacturing and production, and as a result, improvement in products variety, productivity and innovation, all companies and organizations are trying to handle and manage their product in a efficient manner. By identifying new methods in purchasing, warehousing, handling and ordering, all classical processes have lost their applications. These new methods such as Artificial Intelligence (AI) have provided the necessary tools that we need for decision making in specific situations. In this paper, some new definitions in re order point (ROP) have been discussed; in addition we have used Artificial Neural Networks (ANN) for determining re order point for purchasing goods in commercial organizations, especially import companies. For this matter, ANN has been used for decision making in purchasing, and also normal curve has been used for calculating order lead times. In the conclusion, we agreed that our new model has many priorities to its classical kinds.

High-tech companies are rapidly growing in the world. Research and development (hereafter R&D) department strength is the main asset that allows a firm to achieve a competitive advantage in high-tech businesses. The allocated budget to this sector is finite; thus, integration, human resource, risk and budget limitations should be considered to choose the most valuable project in the best portion of time. This paper investigates a case study from a high-tech company in Iran to prioritize the most attractive technologies for the R&D department. The case consists of twenty three technology options and the goal is to find the most attractive projects to sort them out for implementation in the R&D department. In this research, scholars proposed the best–worst method (henceforth BWM) to find the weight of the criteria of the attractive technologies in first step and utilize the newly developed method total area based on orthogonal vectors (henceforward TAOV) to sort the selected technologies based upon the identified criteria. Project integration is one of the least-noticed subjects in scientific papers; therefore, the researchers presented a zero or one linear programming (ZOLP) model to optimize and schedule the implementation procedure on the project risk, budget and time limitation simultaneously. The results indicate that starting few but attractive projects in the first years and postponing the rest to the future, helps a firm to manage funds and gain profit with the least amount of risk.

When considering today’s uncertain atmosphere, many people and organizations believe that strategy has lost its meaning and position. When future is predictable, common approaches for strategic planning are applicable; nonetheless, vague circumstances require different methods. Accordingly, a new approach that is compatible with uncertainty and unstable conditions is necessary. Fuzzy logic is a worldview compatible with today complicated requirements. Regarding today’s uncertain and vague atmosphere, there is an absolute requirement to fuzzify the tools and strategic planning models, especially for dynamic and unclear environment. In this research, an extended version of Strengths, Weaknesses, Opportunities and Threats (SWOT) fuzzy approach has been presented for strategic planning based on fuzzy logic. It has solved the traditional strategic planning key problems like internal and external factors in imprecision and ambiguous environment. The model has been performed in an information technology corporation to demonstrate the capabilities in real world cases.

An important objective of a group decision-making problem is to determine the weights of attributes that are given by experts participating in the decision-making process. Since different decision-makers have unequal importance in decision-making, a series of studies focused on finding a set of appropriate weights for experts participating in a decision problem. In this paper, the problem of weight determination among decision-makers is investigated by extending an algorithm taken from the technique for order preference by similarity-to-ideal solution. In this case, a pair of most compromising and least compromising solutions is derived from individual judgments of decision-makers and then, these solutions are applied as the bases for determining the magnitude of individual alignment with the group opinion by using a closeness coefficient approach. Determining the weights of decision-makers, the group decision-making problem is then solved. Application of the proposed method is illustrated by a numerical example for the selection of a maintenance strategy.

Supply chains have become the major and dominant paradigm of business and competition. The main challenge is how to act in multi-echelon supply chains considering the levels involved. Making a choice independently or integrating with some or all levels will be a critical decision, and therefore affects the overall profit of the chain. This article proposes a non-cooperative game theory approach to helping in making a better decision in the supply chain and gaining the most accessible benefit. Our research considers unlimited three-echelon supply chains with S suppliers, M manufacturers and K retailers. The Nash equilibrium and definition are used bearing in mind inventory and pricing and marketing cost as decision variables for this matter. This paper studies a three-echelon supply chain network and focuses on the value of integrating a pair of partners in the chain. In the decentralized case, the supplier sets its own price, the manufacturer points out order quantity, wholesale price and backorder quantity, and the retailer charges the final retail price of the product and marketing product. Though there are multiple players at a single echelon level, each manufacturer supplies only a specific product to a given retailer. In addition to the decentralized case, two integration scenarios have been taken into account: manufacturer-retailer and supplier-manufacturer. As for manufacturer-retailer integration, inventory/holding cost issues diminish to a single warehouse and the retailer does not have to enforce marketing effort any more. Supplier-manufacturer integration brings similar benefits. Under each scenario, all parties involved simultaneously set their strategies. Through a numerical experiment, 17 design cases (through designing experiments) have been developed and the total profit of the supply chain under each scenario has been evaluated. Statistical tests on the above introduced 17 experiments have found that the decentralized system performs significantly worse than the integration of the supplier with the manufacturer, whereas no significant difference can be observed regarding other combinations.

Supply chain (SC) management aims to increase the overall profit through improvement of various activities and components. Many contradictions between parts and different levels of a SC have been identified in order to achieve overall objectives. Such shortfalls may result in decreased strength and competitiveness of the SC. This paper considers the main conflicts related to inventory, pricing and marketing costs in an unlimited three-echelon supply chain. Aimed at avoiding a profit decrease, the research focuses on finding an equilibrium between inventory, pricing and marketing cost of an unlimited three-echelon SC. On each level, the best leadership option with the greatest payoff is sought for between K retailer, M manufacturer and S supplier. According to Stackelberg non-cooperative game theory, each SC level can become a decision-making leader depending on the available negotiating power. Consequently, three leadership types are modelled on each level and the total SC profit is calculated and compared to ascertain the best option. The authors of the article found that transfer of leadership from a retailer to supplier results in reduction of the total profit. In addition, the research focused on the main effects of parameters used in leadership models. Finally, validation of the proposed model was examined by simulation and Arena software, which indicated that models based on a game theory were performed accurately.