In this paper, we consider a supply chain with multiple raw material suppliers, located in close proximity to each other as a single supplier area, who transport the products to an industrial company, as a single customer at the subsequent downstream stage. The goal of this problem is to determine a schedule to integrate the suppliers’ products transshipment in order to minimize the total cost which includes transportation and inventory costs, subject to the suppliers’ production rate and the customer's daily demands. Following, an integrated transportation system approach, in which all suppliers cooperate with each other by applying a master transportation plan, is designed and evaluated using two linear integer programming models, comparing the integrated transportation model with the non-integrated one. Since solving these models using available commercial solvers is very time consuming, two heuristic algorithms are developed where one of them is combined with two metaheuristic approaches based on genetic and GRASP algorithms. The performance of all developed algorithms are then analysed using randomly generated test instances.

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