madm

The management and performance evaluation system as one of the management processes has a prominent role in helping to achieve the goals and missions of the organization. The purpose of this article is to present a method to evaluate the performance of the organization's task units. This approach, based on a scientific and systematic method, explicitly considers the existence of uncertainty and ambiguity in the nature of organizational activities.

In this paper, a MADM hybrid approach is used. First, the performance indicators have been determined by the literature review and consulting experts, and then the importance and weight of each of the performance indicators has been calculated using the intuitionistic Fuzzy DEMATEL and finally, the performance of organization's units has been evaluated using the ELECTRE intuitionistic Fuzzy method. In order to apply this method, the performance evaluation of the organization of industry, mining and trade of Tehran province has been done with the proposed method.

This study shows the effectiveness of the hybrid intuitionistic fuzzy DEMATEL-ELECTRE approach in performance evaluation the organizational units. This method correctly considers the uncertainty in the performance evaluation indicators by using the intuitionistic fuzzy approach and leads to a correct and reliable performance evaluation. The results showed that among performance indicators, organizational improvement and transformation, transparency and productivity improvement have the most weight and importance in performance evaluation of organizational units.

Originality/Value:

 For the first time, this research has used the hybrid intuitionistic fuzzy DEMATEL-ELECTRE approach to performance evaluation of organizational units. Using the intuitionistic fuzzy approach provides a unique perspective on uncertainty in performance evaluation and increases the reliability of performance evaluation and ranking. The application of this method in a government service organization provides a methodological tool for performance evaluation or rating of organizational units or work teams in different or similar organizations and fields.

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.

IntraditionalSupplychainmanagement,thefocusofthe integrationofsupplychainnetworkisusuallyonasingle objective, i.e., minimum cost or maximum prot. However, the modelling of a supply chain requires more than asingleobjectivesuchaslead-timeminimization,service level maximization, and so on. Sometimes, these objectives may cause con icts such as increasing the service level which usually leads to a growth in costs. Therefore, the aim must be to nd trade-o solutions to satisfy the con icting objectives. In multi-objective optimization problems, there is no single optimum solution, but there is a solution set which creates Pareto optimal solutions. Pareto optimal solutions are a set of tradeos between dierent objectives and are non-dominated solutions, i.e., there is no other solution which would improve an objective without causing worsening of at least one of the other objectives "This paper introduces a bi-objective optimization model of a multi-product multi-periodthree-echelonsupplychainnetworkconsisting of manufacturing plants, distribution centers, and customer nodes. the two objectives are minimization of the total cost while maximizing the average safe inventory levels of manufacturing plans and distribution centers. The goal is to determine the quantities of the products produced by the following: the manufactured plants in dierent periods, number and locations of the warehouses, quantities of products transported between the supply chain entities, inventory of products in warehouses and plants, short safe inventory of product in warehouses and plants, and shortage quantity of the customer nodes. The problem is rst formulated into the framework of a constrained bi-objective mixed integer nonlinear programming model. Then, to solve the problem, two multi-objective decision-making (MODM) methods are investigated. Then, the performances of these methods are compared in terms of both the solution quality and CPU time required in an attempt to select the best one. For this purpose, Statistical hypothesis test and TOPSIS methods are used. Finally, using some parameters, a sensitivity analysis has been carried out to test the sensitivit of the proposed model.