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Purpose - Today, due to the breadth, diversity and multiplicity of investment projects, decision makers and investors are faced with the issue of choosing the most profitable project. The economic rate of return (ERR) index is one of the proper indices that has been presented to determine the profitability of the projects. However, the ERR index has important shortcomings that have led to serious limitations in its use. In this regard, this paper introduces a new measure called the reliable economic rate of return (RERR), which has originated from ERR measure, but it has resolved the drawbacks of ERR index. On the other hand, this paper proposes a new solution by considering the values of the cash flow in terms of fuzzy numbers. After calculating the fuzzy economic rate of return, the profitability potentiality degree of the investment projects can be determined as well as their reliability based on the net present value (NPV) method. Design/methodology/approach - This paper proves that if we equate the initial cash flow of investment projects with the sum of the negative values of the relevant cash flow stream, then the RERR value would be greater than '-1'. In this regard, this paper proposes a solution to modify the initial and final values of the investment cash flow stream, merely without changing middle values. Thereby, the NPV of the modified cash flow does not change. On the other hand, it is sometimes difficult to estimate the values of cash flows as a crisp number, which may lead to a wrong decision in accepting or rejecting projects. For this purpose, this paper considers the values of cash flow stream as fuzzy numbers and describes a solution for calculating the fuzzy RERR using the α-cut method and the RERR index. The proposed solution is compatible with the NPV method and also has fewer calculations than the other methods. This paper also proposes a method that calculates the profitability potentiality degree of projects and provides more comprehensive information to the decision makers by examining the intervals obtained from cutting the fuzzy values of the projects and presenting a new and reliable solution. Findings - Using the @RISK software, it was found that the estimation of fuzzy return rate using RERR index and α-cut method is very close to the simulation result. It confirms the appropriate accuracy of the proposed solution. Also, the results obtained from the software in determining the profitability of projects indicated that the proposed solution is more accurate than the methods of 'comparison of the expected intervals' and 'strict exceedance possibility'. It is also fully compatible with the NPV method. Research limitations/implications - In this research the market rate is assumed constant, while, in practice it can vary over the periods. Defining the market rate as an inconstant parameter, using the robust optimization approach and investigating the subject of this paper under other uncertainty environments are future study suggestions to both researchers and practitioners. Practical implications - One of the most important applications of this study is in risky projects wherein estimating the values of cash flow stream as a crisp number is difficult. The results of this paper help decision makers in reducing risk and determining the project profitability. It is worth mentioning that the solution proposed in this paper can be used for all projects with any cash flow stream value. Social implications - Failure to make the correct decision regarding the acceptance or rejection of the projects could have major negative consequences for the companies, organizations and even society. This paper helps decision makers, investors and organizations to determine the projects profitability that could benefit organizations and society. Originality/value - This paper proposes the RERR measure as a profitability index such with several favorable properties: (ⅰ) it exists and is unique, (ⅱ) it is NPV-consistent in accepting/rejecting decisions, (ⅲ) it provides values greater than '-1', (ⅳ) it takes into account all of the project's outflows which may be regarded by some practitioners as an appropriate indicator of the overall investment. Furthermore, this paper proposes an appropriate method for calculating the fuzzy RERR and a new method for determining the profitability potentiality degree of the investment projects based on the NPV method. [ABSTRACT FROM AUTHOR]

Background and objectives: Climate change has been a serious issue in the last two decades and many studies have focused on its various aspects. Determination of future habitat of rangeland species status in present and future years by climate warning models seems necessary. It is the aim of the study to investigated whether the increasing temperature will have a positive of negativ effect on the presence of species in the habitats. Methodology: Using 19 bioclimatic variables and three physiographic, in logistic regression model climate change in the next three decades (2050) and its effects on the current change of Ferula ovina species and the future, was examined and a map was created. Output maps were also grouped into four categories with a probability of occurrence between zero and one. These groups, were unsuitable habitat, (0- 0.25); Habitat almost suitable, (0.25-0.5); highly suitabel (0.5-0.75) and a very high (0.75-1). Finally, by referring to the coefficients of climatic variables and topography in regression relations, effective variables for the current and future range of F.ovina were introduced. Results: Based on the results; among the climatic and topographic variables, only the indicators related to the average temperature of the warmest season (BIO10) and the average temperature of the coldest season (BIO11) were identified as effective factors on the distribution of F.ovina species in present and future Alborz rangeland habitats. Milder (Rcp4.5) and pessimistic (Rcp8.5) scenarios shows that average annual temperature in places with a probability of more than 75%; over the next three decades rise from 2.6 to 0.3 °C. The height of suitable habitats will be 60 to 162 meters above sea level. Under climate scenarios, 15% of suitable habitats will be lost by 2050 and current unsuitable habitats will increase by 48%. Overall; climate change and increasing temperature characteristics will cause the vertical expansion of F.ovina species to higher latitudes along the altitude gradient. This indicates that over the next three decades, the presence of F.ovina species in the habitats of the region will decrease and the risk of its removal from the southern Alborz ecosystems is evident. Conclusion: According to the results, large changes in the distribution of this species are expected to occur under climate changes. These changes are such that they can limit the suitable climatic conditions for the life of this important and effective species in the southern Alborz rangeland habitats. To improve the conditions, the least that could be done is to control the degradation of F.ovina species habitat, by managing livestock grazing and preventing land use change. If a protective approach is applied; Collecting seeds and storing them in the gene bank of natural resources, introducing superior and drought-tolerant ecotypes with better structural and functional traits and preparing strong seeds from them are recommended. [ABSTRACT FROM AUTHOR]

In this paper, the problem of scheduling jobs with non-identical sizes has been studied on a single-batch processing machine, in order to minimize the makespan. Using new lower bounds, a branch and bound algorithm has been proposed to solve the problem. In this algorithm, two new methods have been used to generate lower bounds and results have been compared with the existing lower bound in literature. In order to evaluate the performance of the proposed method, test problems have been randomly generated and branch and bound algorithm has been tested with different lower bounds on these cases. Findings indicated that when the size of the jobs is large compared to the capacity of the machine, the branch and bound algorithm with the new lower bound has the best performance. When the size of the jobs is small compared to the capacity of the machine (up to half the capacity of the machine), the algorithm with existing lower bound has better performance. In addition, when the size of the jobs is neither large nor small, the lower bounds provide the best performance. Introduction: Based on predictions, services are a key component of the growth of the global economy in future (Arnold et al. 2011). Acording to Jane and Kumar (2012), services play a critical role in a supply chain. Also, according to Wang et al. (2015), a "product" or "service" must exist in each supply chain which is produced by the upstream sectors and delivered to downstream. Recently due to increasing customer expectations, companies’ competition has been replaced by the supply chains competition and as a result, competition has been increased in the simultaneous supply of products and services. This has led to challenges in integrating companies and in coordinating the materials, information and financial flow that were previously overlooked. Accordingly, a new managerial philosophy has been developed known as Product-Service Supply Chain (PSSC) (Stanley & Wisner, 2002). This study seeks to develop a performance evaluation model for the product-service supply chain in the home appliance industry, which is finally solved using Adaptive Neuro-Fuzzy Inference System (ANFIS). Design/Approach: In this paper, performance evaluation constructs and criteria of service supply chain are identified by reviewing the literature and exploratory and confirmatory factor analysis and then, the performance evaluation of service supply chains in Iran's home appliance industry has been performed using these constructs, criteria and ANFIS. Findings and Discussion: Based on the findings, ten main extracted constructs can be suggested for the performance evaluation of the supply chain. They include "Operational Performance (OP)", "Strategic Performance (SP)", "Financial Performance (FP)", "Performance of Information and Communication Technology (PICT)", “Return Performance” (REP), “Risk Performance (RIP)”, “Logistic Performance (LP)”, “Market Performance (MP)”, “Internal Structure Performance (PIS)” and “Growth and Innovation Performance (PGI)”, among which, the Strategic Performance (SP) and Return Performance (REP) are the most important and the least important constructs, respectively. Conclusions Based on the findings, the following practical recommendations are suggested to the companies: · Enhancing the demand forecasts performance and utilizing more appropriate methods and software to improve forecasts in demand and order management areas. · Improving the return management status by increased attention and more investment in return management processes. · Effective investment in service development management to enhance the R&D services performance. · Utilizing risk management approaches and methods to identify and take preventive actions on the risks in the companies’ service supply chain. [ABSTRACT FROM AUTHOR]

The aim of this study is to propose a comprehensive performance evaluation model with emphasis on service performance metrics in the service-product supply chain rather than the production supply chain in the home appliance industry and using neural-fuzzy networks for performance evaluation. The present study is typically a descriptive-exploratory research with survey approach in which, data analysis has been conducted using quantitative method and exploratory and confirmatory factor analysis. For the purpose of this study, a sample of 58 home appliance companies has been selected and Smart-PLS, SPSS and Matlab software have been used for data analysis. Findings indicated 10 main constructs and 29 performance criteria obtained for evaluating the performance of service supply chain and fuzzy neural networks of several home appliance companies. Introduction: Based on predictions, services are a key component of the growth of the global economy in future (Arnold et al. 2011). Acording to Jane and Kumar (2012), services play a critical role in a supply chain. Also, according to Wang et al. (2015), a "product" or "service" must exist in each supply chain which is produced by the upstream sectors and delivered to downstream. Recently due to increasing customer expectations, companies’ competition has been replaced by the supply chains competition and as a result, competition has been increased in the simultaneous supply of products and services. This has led to challenges in integrating companies and in coordinating the materials, information and financial flow that were previously overlooked. Accordingly, a new managerial philosophy has been developed known as Product-Service Supply Chain (PSSC) (Stanley & Wisner, 2002). This study seeks to develop a performance evaluation model for the product-service supply chain in the home appliance industry, which is finally solved using Adaptive Neuro-Fuzzy Inference System (ANFIS). Design/Approach: In this paper, performance evaluation constructs and criteria of service supply chain are identified by reviewing the literature and exploratory and confirmatory factor analysis and then, the performance evaluation of service supply chains in Iran's home appliance industry has been performed using these constructs, criteria and ANFIS. Findings and Discussion: Based on the findings, ten main extracted constructs can be suggested for the performance evaluation of the supply chain. They include "Operational Performance (OP)", "Strategic Performance (SP)", "Financial Performance (FP)", "Performance of Information and Communication Technology (PICT)", “Return Performance” (REP), “Risk Performance (RIP)”, “Logistic Performance (LP)”, “Market Performance (MP)”, “Internal Structure Performance (PIS)” and “Growth and Innovation Performance (PGI)”, among which, the Strategic Performance (SP) and Return Performance (REP) are the most important and the least important constructs, respectively. Conclusions Based on the findings, the following practical recommendations are suggested to the companies:  Enhancing the demand forecasts performance and utilizing more appropriate methods and software to improve forecasts in demand and order management areas.  Improving the return management status by increased attention and more investment in return management processes.  Effective investment in service development management to enhance the R&D services performance.  Utilizing risk management approaches and methods to identify and take preventive actions on the risks in the companies’ service supply chain. [ABSTRACT FROM AUTHOR]

Optimal portfolio selection and how to invest in, is one of the key issues which is considered in the capital market and should be paid attention by investors. In this regard, investors studies in selecting optimal portfolio accords to risk and return level. What has been done in the field of financial calculations and portfolio selection should prioritize existing investments in terms of risk and return respectively, until investors be able to constitute their optimal portfolio according to the finance and their level of risk-taking. Hence, measuring risk is considered as a major issue in the investment of portfolio. So in this research which was done in a capital market of Iran, it is presented a multi objective single - period mathematical model for measuring the risk of portfolio which integrates measure of return and two measures of risk (semivariance, Cvar). This model enables investors to measure the risk of portfolio carefully under transactions cost constrains and invest in a portfolio with maximum rate of return and minimum rate of risk Results show that using integrated risk measure can increase the carefulness of investors in capital market for optimal portfolio selection. [ABSTRACT FROM AUTHOR]