Journal of Operational Research in its Applications
Year:2017 | Volume:13 | Issue:4 (51)|Papers Count:8

Over the past few decades, the environmental concerns about the production operations industries has been forced various organizations to use green practice in the different processes of the supply chain because of green supply chain management as a critical organizational philosophy in reducing the environmental hazards and a preventative approach to increase environmental performance and achieve a competitive advantage in the organization. The main goal of research, the structural model design green supply chain management practices in the field of Iran's oil industries. ‘To study literature and benefiting from textual content analysis approach the number of fifteen green actions was enumerated to localization them in the field of petroleum industries of the Delphi technique was used in three rounds. Statistical population this research formed of managers and experts working in the field of oil industry and familiar with the issue. Sample members were selected with target non-random sampling method of kind judgment. A questionnaire was used to collect data that it was confirmed its validity and reliability. To design the structural model green practice to used interpretative structural modeling approach in the fuzzy environment for managing uncertainty in the language of the judgments. The results of the modeling and MICMAC analysis showed that legal requirements and regulations, and internal environmental management, design green, and green technology are the practice effecting of in green supply chain management.So, it is suggested to Managers which have more emphasis on this category of practices.

Flexible job shop scheduling has drawn the attention of many researchers. This paper examines the flexible job shop scheduling problem, considering sequence dependent processing times and assembly case. The aim is to determine the operations assignment to a set of machines and to identify their processing priority to minimize total completion time of the final products. Meanwhile and since the problem is not studied in the subject literature; the mathematical model of the problem is developed, initially. Due to the NP-hardness, being the problem, three meta-heuristic algorithms, including genetic algorithms, simulated annealing and a hybrid algorithm that combines the two previous algorithms is presented to solve the problem. Finally, a comparison is made among these algorithms. The computational results show that the hybrid algorithm gives a better performance than the others.

Portfolio selection always has been one of the interesting subjects in financial problems and markets. In this paper, a novel logical and useful model for optimizing portfolio is proposed that this model have some constraints such as flexibility in stock's weight that don't determinate a fixed and solid bounds for stock's weights in portfolio optimization problem and also, cardinality constraint is applied for portfolio problem. Then fuzzy programming applied to handle uncertainty of stock returns and with flexible and possibilistic programming, that both of these methods are categories of fuzzy programming, proposed model converts to a crisp one. The proposed model for evaluating, performance testing and logicality approved, is applied to some monthly return of companies stock of Tehran Stock Exchange and the results is reported. The results showed that in lower values of confidence level in proposed portfolio problem, it's possible to obtain a higher profit with low risk.

The several methods have been developed to financial statements analysis during recent decades; for example, one of the most recent methods is data envelopment analysis method. But this method has a restriction because it does not consider the time factor in calculations and it processes the financial performance at specific time and at static analysis, accordingly, this method is not able to assess the decision units at different time periods. for this reason, this research represents the new model namely Time driven data envelopment analysis model. In this research, 100 companies among companies accepted in Tehran securities exchange was selected to test the model during the periods between 1384-1389. The results of this model showed that this model was able to process the financial statements during time, also, results showed that among companies under study, only the Iran Automobile Parts company could protects its whole efficiency during the 6 years.

These days efficiency analysis of electricity distribution companies is an important matter to legislators. Movement to privatization and reconstruction of electricity industry increases its significance. Totally, parametric and nonparametric methods are used to evaluate the performance of electricity distribution companies. There are some weaknesses about seperation strength and sensitiveness of efficiency frontier to outlying data in DEA methods. So, in this research, mixed Neural-DEA methods are used as two nonparametric methods to evaluate 39 electricity distribution companies of Iran in 2010. Comparing the results of Neural-DEA and DEA models show high power of Neural network to measure its efficiency.

The main assumption in Window Data Envelopment Analysis is that there is not any frontier shift among observed periods. But examining this assumption is neglected in many researches. In this study we apply nonparametric statistic tests, (Wilcoxon between two periods and Friedman between more than two periods), for examine whether any frontier shift occurs among observed periods. As an important case study, this research applies this technique to evaluate efficiencies of 5 faculty of Islamic Azad University in Kerman branch, between 1385 until 1391. Applying the statistic tests, shows that there is one frontier shift among 1387 and 1388. And facilities rank as this order: Microbiology, chemistry, math, physics and computer. Because university has five teaching programs we use Analytic Hierarchy Process (AHP) to determine relative importance of these programs for departments and to find weights for making their data equivalent.

One of the main factors in today's competitive environment sustainability, reduce production costs and product. Select appropriate providers can significantly reduce production costs and increase the competitiveness of the organization, because in most industries, the cost of raw materials and product components, covers much of the cost of the product. In this article we are trying to identify issues affecting the supplier selection criteria and determine their importance in our approach combines supply chain Large examined. Large supply chain approaches attempt lean, agile, resilient and green supply chain management space to sit together and at the same time enjoy the benefits of each one of them to cover their shortcomings. To determine the importance and ranking criteria fuzzy network analysis process. This research is based on objective, functional and based on their nature descriptive.

Today, organizations spend significant budgets for creating and maintaining relationships with their clients to maintain and improve its position in competitive markets. Since, marketing managers have challenges for allocation of available budgets and selection of best innovative actions, the efficient analysis of customer behavior to allocate resources is essential. This paper proposes a two-stage model for portfolio customer management using DEA and robust optimization. In the first stage, the performance of all customers is evaluated by robust BCC model and appropriate customers are selected as candidates for the optimal resources allocation. In the next stage, the optimal allocation is done with the objective of maximization customer lifetime value to marketing expenses ratio. The proposed model was implemented for customers of Bhban manufacturing company that operates in the medicine industry and the results were analyzed. The main contribution of this research is use of data envelopment analysis and robust optimization for customer performance evaluation simultaneously. The results showed that using this approach, customers who are candidates for the final basket in resource allocation have more expected value than other approaches in the literature.