This paper investigates an integrated scheduling of production and distribution activities in the supply chain where both machine deterioration and learning effects have been consequently addressed. Manufacturer aims to minimize… Click to show full abstract
This paper investigates an integrated scheduling of production and distribution activities in the supply chain where both machine deterioration and learning effects have been consequently addressed. Manufacturer aims to minimize the total weighted completion time, while a distributor focuses on reducing shipping times with batch delivery by using capacitated vehicles. The aim of this problem is to minimize the sum of weighted completion times plus total delivery times. First, a mixed integer linear programming model is proposed. Then for a special case, a branch and bound algorithm is developed with utilizing the structural features of the problem. In order to solve large-scale instances of the general problem in a short/reasonable time, a simulated annealing algorithm is provided. Computational results show that the proposed heuristic techniques have high efficiency to achieve the optimal solution, and that they are useful to solve large sizes of the problems at a short time. Finally, by providing a real-life case of wax manufacturing and its distribution system, it is shown that the application of integrated decisions can significantly reduce costs imposed on the firms.
               
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