Journal of Operational Research in its Applications
Year:2018 | Volume:15 | Issue:3 (58) |Papers Count:10

One of the fundamental concepts in convex analysis and optimization is the relative interior of a set. This concept is used when the interior of a set is empty due to the incompleteness of its dimension. In this paper, first, we propose a linear programming model to find a relative interior point of a polyhedral set. Then, we discuss the application of this model to geometric programming. Specifically, we show that a special form of our proposed model can determine the degeneracy of a geometric programming problem by identifying a relative interior point of the feasible region of its dual. Finally, we present two numerical examples for describing the applications of the proposed model.

Relief research centers have an important place in promoting science and technology nationwide. On the other hand, given the limitations in allocating the funds and the facilities needed to establish these centers, it is important to decide on the selection of priority centers. In this decision-making process, several factors, such as requirements, priorities and strategies, capabilities, and balanced and sustainable development, should be considered. The total of the above items will make decision-making on ranking and selection of proposed projects a complex, time-consuming and cost-intensive resource. To this end, designing and developing a decision support tool is considered. In this research, a DSS is designed and evaluated to assess the design of research centers for Islamic Azad University units. This decision-making system, based on information from research centers and indicators gathered by experts, as well as the history of successful and failed research centers, is better explored with the audit tool and data envelopment analysis (DEA), and ultimately help for prediction. Finally, it is investigated that weather the research center of the applicant is can makes improvements or not.

Today, with the development of a competitive environment attention to supply chain management has become a key issue in the commercial organizations. It has influenced all organizational activities ranging from raw material purchasing, production, reducing cost and after-sales service, etc. On the other hand, by increasing the volume of pollutants and increased attention to environmental issues, manufacturers have to expand their supply chains into a closed-loop supply chain (CLSC). In this paper, we attempt to deal with the environmental issues presented in the design of CLSC networks. For the consideration of environmental issues in the proposed network, we plan an integer nonlinear programming and use the GAMS to solve it. This model optimizes the flow of sectors and products in the CLSC and the number of trucks used for the forward supply chain. Finally, applicability of the proposed model is tested via a real case study in refrigerator manufacturing plant, and the results are analyzed in depth. The application of the developed model can help to increase companys’ profit by reducing transportation costs while reducing environmental impacts and creating a green image of the supply chain.

One of the important tasks of universities that are usually challenging is university course timetabling problem. They are faced with this problem every year and every term and which is directly effective on education performance. In the university course timetabling problem, the university sources including lessons, lecturers, classes and other teaching sources are assigned to a series of time slots. If they are assigned properly, educational quality can be enhanced. Given the importance of this issue, a new mathematical model is proposed in this study for university course timetabling. Indexes of educational quality such as quality of lecturers in teaching, considering the counseling time for the students and appropriate time of lesson presentation during the day are taken into account in this model. Considering that university course timetabling problem is at big NP-Hard dimension, a meta-heuristic algorithm is employed based on non-dominated sorting genetic algorithm. Given that the algorithm proposes several ranked solutions, the final solution is selected via defining some indexes to measure quality of solutions and used multi-criteria methods. Finally, course timetabling of graduate studies for the Department of Industries at the Islamic Azad University-Najaf Abad Branch was determined via this algorithm.

The discriminant analysis tries to find an equation based on a current order in the data that can be commented about the membership of a unit in one of the two or more groups according to the number of the independent variables. DEA-DA and logistic regression are among the discriminant analysis techniques which have no complex statistical assumptions and are applicable in many studies. On the other hand, Tobin's q index is one of the widely used financial indicators used as a benchmark to evaluate performance. But also there are some ambiguities in the accuracy of the calculation of this index that many researchers have tried to resolve the ambiguity of the index and improve performance. The current research has also sought to provide appropriate discriminant function of Tobin index for the accepted companies by Tehran Stock Exchange based on associated financial ratios widely used by such an index. Therefore, after finding indices related to Tobin's q, the data of 181 companies listed in Tehran Stock Exchange in the financial year leading to 29 of Esfand in 1393, DEA-DA and logistic regression were run in parallel and compared with obtained results and a number of indices were removed which in both methods from the mathematical and statistical point of view had instable conditions, once again two methods were implemented with 5 independent variables that better and more stable outputs were observed in both of the methods. The results have been reported and analyzed.

The importance of social performance of corporate and business units has increasingly been emphasized by researchers and practitioners in recent years. Since green supply chains play important roles in decreasing the pollution of business and corporate environments, social performance has a significant role in creating this supply chain; Therefore, in designing green supply chain social performance should be considered carefully. This paper addresses designing a model of social performance for green supply chain under uncertain conditions. To this end, first a multi-objective fuzzy mathematical programming model is designed. In this model, the objective functions include minimizing the costs and environmental impacts and maximizing the green supply chain of the social performance. To solve this model, an interactive fuzzy solution method is used. Finally, a real industrial case study is provided to measure the validity and effectiveness of the model.

In this paper, we study the problem of pricing multi-asset American-style options in the Heston-Hull-White model. It is widely recognized that our intended model compared to the original Heston model, due to its stochastic interest rate and stochastic volatility, is more compatible with the realistic of the market. We demonstrate the efficiency and accuracy of the our proposed method by verifying the effect of the interest rate and volatility levels on the multi-asset American put option price under the Heston-Hull-White model.

Communication plays an important role in the growth of societies and people. The Postal network is considered to be the largest physical link and network of exchanges among communities in the world, which is of particular importance for continuous communication with customers in these types of service units. In contrast, prediction, control and analysis have become an inevitable necessity in organizations and a great management tool for decision making. In this paper, basic data envelopment analysis models for measuring and evaluating post offices’ efficiency in Guilan province in years 1392 & 1393 have been investigated. For this purpose, the input-oriented CCR model is better than the BCC model. Because the traditional data envelopment analysis models are not capable of introducing the optimization model and the most efficient unit, we use Anderson-Peterson’ s model, in which Rudsar & Anzali units are best at 92 and 93 consecutives. Finally, we use the neural network to integrate the data access approach for predicting the efficiency of postal units. The results show that this new model has good potential for prediction, and because of its high precision, it can replace traditional methods.