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"ABSTRAKThe Fuzzy Fixed Charge Transportation Problem in which both fixed and transportation cost are fuzzy numbers is considered in this paper. Due to NP-hardness of the problem, we utilize three types of Electromagnetism-like Algorithms (EM), Genetic Algorithm (GA), and Simulated Annealing (SA) which are firstly being proposed and comprised in this research area. Besides, our other novelty approach is the use of new encoding mechanism, namely string representation, for the first time which is employed for the problem and can be used in any extended transportation problems. Also, the last version of EM is being firstly developed and proposed in this paper. The employed operators and parameters are calibrated to ensure the best performance of the algorithms. Besides, different problem sizes are considered at random to study the impacts of the rise in the problem size on the performance of the algorithms."

"This paper addresses a new robust multi objective multi period model for supply chain planning under uncertainty considering quantity discounts. The proposed model maximizes the current proht of the distributor by making a balance between the total costs of the supply chain and the distributor company s revenues of selling products and also maximizes the company s expected profit by introducing brands and taking the risk of loss on it. Considering uncertainty in the purchasing cost, selling fees, and demand fluctuations, the new robust multi objective mixed integer programming model is solved as a single objective mixed integer programming model by utilizing the LP metrics method. By settling regulatory penalty parameters and considering different economic scenarios, the robustness and effectiveness of the developed model are verified with the data from BEH PAKHSH Company, a commodities distributor in Iran. The outcomes show that the proposed model is a promising approach to run an efficient supply chain."