نشریه تصمیم گیری و تحقیق در عملیات
سال پنجم شماره 3 (پاییز 1399)

In this paper, the -product and t-state uncapacitated facility location problem is investigated. To be more precise, it is assume that each customer can request  different products in a -state network. First, the mathematical formulation for the -product and t-state uncapacitated facility location problem with certain costs is proposed. Also, it is shown that this paoblem is NP-hard. Since in most real-world problems the input of data are often ambiguous and uncertain, we study the -product and -state uncapacitated facility location problem in which the facility set-up costs and customer service costs are fuzzy random variables. Using three criteria, ‎probability-possibility‎, ‎probability-necessity‎ and ‎probability-credibility, the -product and‌ -state uncapacitated facility location problem is formulated as a quadratic programming. Finally, a practical example is given to illustrate the efficiency of the proposed approaches.

Data envelopment analysis is the most widely used mathematical model to evaluate the efficiency of decision units. Classical and simple network models in data envelopment analysis are not able to calculate the efficiency of multi-stage and sequential supply networks. These types of networks include several successive structures and components, such as the 5-level supply network, which are used in many strategic industries. The distinction between this structure and the sequence of supply networks with several components over time as well as the relationship between the efficiency of a time period and the total efficiency during a time period is examined. The purpose of this paper is modeling in the form of developing a non-radial SBM model and presenting a dynamic data envelopment analysis model to evaluate the performance of a sustainable supply network as a wide and multi-level network so that efficiency can be calculated at five levels of supply network as well as periods. Provide consecutive. The model presented in the 5-level supply network in the cement industry has been validated. The results showed that the new model performs a logical and close to reality evaluation compared to the classic and static network models.

In this paper, a closed-loop supply chain for pharmaceutical items consists of a pharmacy, a distribution center, a recycling center and several pharmacy sites is considered in which two types of routing are performed. The first involves the routing of vehicles between the distribution center and the pharmacies, and the second involves the routing of vehicles to the recycling center and all nodes. Two types of pharmaceutical items are considered for this purpose, and their demand varies for different periods. The distribution center can offer discounts depending on the pharmacy orders. In addition, the distribution center can increase its capacity by renting more warehouses. Also, we have two objective functions: minimizing costs and environmental pollutants caused by carbon dioxide emissions. This problem is solved in the small-sized problem by the Epsilon constraint method and in the large cases by two hybrid algorithms based on the Fordyce-Webster algorithms and NSGAII-FW and MOSA and evaluated by different criteria. The computational results show that the NSGAII-FW algorithm is more efficient than the MOSA algorithm.

Developing the right sourcing strategy in corporate supply management is so critical for today's executive managers. Manufacturers must be aware of the complexities and risks of sourcing at a competitive cost to ensure the availability of long-term materials and components. They have to deal with uncertainty and supply/price trade-off. This can lead to a variety of supply strategies including concurrent outsourcing in addition to the strategy of sourcing. After classifying the selected items on the basis of Kraljic supply portfolio model, 39 factors affecting sourcing were identified according to three approaches concerning “risk management”, “Resource Base View” and “Transactional Cost Theory”. Then the above-mentioned factors were screened and localized according to the Fuzzy hypothesis test questionnaire and finally, 15 criteria were selected. In the next step, the relationships obtained from the DEMATEL method were used for the Analytic Network Process to determine the weight of each indicator. Then, according to the weight of each indicator, the decision was made on how to supply each group of items through the PROMETHEE questionnaire and the results were compared with Kraljic instructions. Finally, according to the results, the relevant strategies of sourcing were suggested based on Kraljic model. The best strategy for the group of “strategic goods” was related to internal production. If the goods are classified on the group of “leveraged and non-critical” it will be better to outsource. Finally, the most suitable strategy for the group of “bottleneck goods” is concurrent sourcing.

The oil consortium in Iran is one of the most important approaches to implementing the huge projects of the petrochemical industry. But the selection of suitable and expert partners is one of the most common bottlenecks in such cooperation networks. The purpose of this paper is to provide a practical, yet simple, solution for the decision makers to be able to choose the right candidate from the selected candidates. For this purpose, a three-stage model has been designed. In the first stage, the criteria affecting the choice of partner from the perspective of experts and reviewing the literature were first collected and weighed with the help of SWARA method. In the next stage, the ranking of partners (6 domestic and 4 foreign companies) was based on a set of decision-making methods such as COPRAS, VIKORA, SWA, TOPSIS, ARAS, MOORA, and multi-MOORA. The final stage integrated the ranking results based on the Copeland. In the end, financial capability and debt ratio and repayment potential were introduced as the most important criteria and sub-criteria. Also, partner 3 was selected as the best candidate by Copeland. Finally, in order to measure the performance of the integration of results, the Spearman correlation coefficient was used and the results of high test affinity and integration of results were obtained. Therefore, it can be said that the approach used has performed well.

Total covering problem is one of the most commonly used issues of locating facilities. In this context, the goal of determining the P service center is to cover at least the cost of deploying all demand points. These issues have a wide range of nature and scope, each of which is optimized by taking into account certain conditions in order to find the answer. One of these conditions can be a situation in which, in addition to full coverage of demand, the dispersion of facilities is also considered. Facility dispersion means maximizing the distance between facilities with respect to existing limits. This research seeks to provide a suitable model considering the predictable limits of the real world and the use of an appropriate method for solving the cover-dispersion model. Accordingly, the full coverage of the solution space and the choice of the optimal location of the facility with maximum dispersion, taking into account the minimum number of facilities and the lowest cost of deployment, due to the limited capacity of facilities and the minimization of transportation costs are the goals of this research. Due to the NP-HARD nature of the coating and literature models, solving these models, an algorithm is designed based on the genetic method for solving the model. In order to improve the quality of the algorithm's parameters, the parameters of the algorithm are set by the Taguchi experimental design method. The results show that the algorithm is suitable for the model.

Increasing competition in the insurance industry has made most industry executives think of ways to stay in business, so they have to look for ways to increase their sales and other goals, including attracting customers. Such as; reducing costs, quality of service, proper behavior of employees, reducing administrative bureaucracy, reducing the time to do customer work when entering the company, reducing the time to pay compensation to the customer and innovation to gain competitive advantage and so on. Therefore, the purpose of this study is to predict and rank the factors of customer attraction in Mellat Insurance Company of Shiraz during the three years 2019 to 2021. For this purpose, the system dynamics model and network data envelopment analysis have been used. In order to formulate the factors of customer attraction, first the causal-loop diagram and then the stock-flow diagram were simulated. Then, this operation was performed for different scenarios and the simulated results were entered as the input of the network data envelopment analysis model. Based on the obtained result, the best and most efficient factors of customer attraction were selected and the interaction of these factors and their impact and the success of customer orientation was addressed.

Data envelopment analysis is a suitable and useful technique for measuring and evaluating the efficiency of decision-making units. This technique is also an effective tool in evaluating the efficiency of units in auditing. Therefore, the purpose of this paper is to evaluate the efficiency of audit firms in terms of audit quality by using data envelopment analysis. Theoretical foundations and data of this study are based on library studies of the pharmaceutical industry of companies listed in the Tehran Stock Exchange. In this study, the output variable is audit quality and input variables include the number of partners of auditing firms, audit fees and auditing hours. The results, using the cross-functional method of data envelopment analysis, show that Behmand, Azmoodeh Karan and Arvin Argham Pars have the first to third ranks in terms of efficiency. Evidence from this study confirms that data envelopment analysis can be used as an appropriate method for analyzing the efficiency of audit firms in in order to assess the quality of auditors' work to support investors by financial analysts and capital market policymakers.