Supply chain consists several components which are involved with customers in terms of production and servicing. Supply chain management is one of vital research area raised in recent years. The main challenge in supply chain is coordination and integration among its components. Because as integration of chain component increases, costs are reduced consequently. In this research, coordination and integration in a supply chain which includes a production facility and a vehicle for delivering the orders to a set of customer, is studied. The integration aims to minimize tardiness of orders and delivering cost. . The proposed problem has complexity of strong NP-hard, and it has been investigated for the first time. To solve the problem with exact methods, a mixed integer programming model is developed. Due to the high complexity of the problem, proposed MIP model is not able to solve the problem in a reasonable time. Thus, two metaheuristic approaches is developed to solve the large size problems: Iterated local search (ILS) and genetic algorithm (GA), which both of them are novel and innovative according to the specific characteristics of the problem. Also, in this research, computational methods is used to check the performance of developed algorithms. In order to analyze the results, analysis of variance (ANOVA) technique is utilized. Computational results verifies the efficiency of metaheuristic approaches. Finally, result are shown that ILS performs absolutely better than GA.
