Journal of Industrial Engineering and Management Studies

Abstract In today's world, supply chain discussion or performance evaluation debate is one of the most important issues in any industry. Performance evaluation refers to a set of actions and information that is implemented to increase the level of optimal use of resources and facilities in order to achieve goals in an economical manner combined with efficiency and effectiveness. Generally, the performance management system can be considered as a process of measuring, evaluating and comparing the amount and manner of achieving the desired status and, finally, improving performance. In this research, the efficiency of 7 units of the Iranian Electric Motors company is addressed using data envelopment analysis. To assess the company's efficiency, it has been used some parameters include intermediate cost, manpower costs, depreciation cost, value of outputs and value of data, and two outputs of factor productivity and competitiveness. So, using the data envelopment analysis, the efficiency of the model was obtained and the weighted criteria were calculated by the fuzzy TOPSIS multi-criteria decision-making method. Given that these supply chains are considered as the statistical society of the electromotor industry, and given that the average technical efficiency is 0.584, it can be concluded that the industry faces 0.416 technical inefficiencies, in its turn, it is a high value.

Abstract By providing timely transportation and dispatch of raw materials and finished goods, freight transport plays an essential role in industries, commercial activities, and trade war industries. It also has a significant impact on the overall performance of associated organizations and the ultimate costs of their products. Therefore, freight transport providers are under pressure to decrease costs and increase their service levels and should overcome these pressures by redesigning and improving their logistics processes on strategic, tactical, and operational levels. In this research, a multi-objective model is proposed for hub location in the field of war equipment under uncertainty. The first objective is to minimize costs, the second objective is to maximize the fulfillment of demands, and the third objective is to minimize congestion on the routes. Taking into account the parameters in the state of uncertainty, the mathematical model is modeled in a robust state and a robust counterpart model of the problem is proposed. In order to solve the problem on a small scale, the exact epsilon constraint method is used in GAMS software. Also, meta-heuristic approaches of grey wolf optimizer (GWO) and non-dominated sorting genetic algorithm (NSGA-II) are used to solve the model in medium and large dimensions. Next, the solution time of two algorithms was compared. 10 numerical experiments with different dimensions were designed and implemented through GWO and NSGAII algorithms. The results showed that the time to solve the GWO problem is less than the other algorithm. Finally, proper performance indicators are used to compare the performance of the used algorithms, and as a result of solving several numerical examples and calculating their performance indicator, it is concluded that the GWO algorithm has a better performance in solving the model.

Abstract In today's world, international exchanges have become more prosperous due to trade and globalization. In this competitive environment, availability of products is as important as price, quality of materials, and construction. This issue doubles the importance of logistics in today's era. In this paper, a new hybrid multi-criteria decision-making MCDM technique for choosing third-party logistics service providers is developed. With having the necessary capacities and facilities, third-party logistics, or 3PLs, can take on logistic activities in a specialized manner so that manufacturers can focus on the important issues related to production optimization. To outsource logistics activities, evaluation, ranking, and selection of 3PLs are strategic decisions. By using the BWM, Best-Worst Method, the identified criteria were weighted to evaluate the financial and operational performance of third-party logistics companies. After that, the EDAS technique was used to rank 3PLs listed on Tehran Stock Exchange. According to the calculations made in this research, Tidewater Co was ranked first, Iran Shipping Co was ranked second, and Tuka Transport, Persian Gulf Transportation, and Rail Seyr Co was ranked third to fifth.