Supply chain management is an important topics in both the theoretical and practical aspects that many researchers have considered it. In the traditional supply chain, Raw materials are prepared, then orders are produced on one or more production equipment and shipped to warehouses or distribution centers for intermediate storage and finally delivered to customers or retailers. In fact, scheduling and distribution are considered separately and independently of each other. In the justify; MARGIN: 0cm 0cm 8pt" This problem is NP-hard. For this problem, two mathematical modeling including a non-linear and linear model and a heuristic approaches for solve it are presented. Since the problem is NP-hard and inability models in high-dimensional problems, two meta-heuristic methods are introduced. Various computational tests have been used for evaluating the developed methods .Experimental design techniques for generate experiment and to analyze results, analysis of variance have been used. Computational test results show that heuristic and meta-heuristic methods presented in this thesis are high performance also between presented algorithms, adaptive genetic algorithm has better performance than other algorithms.
