Coordinated Multi-plant Production Planning in a Multi-echelon Production Environment Considering Alternative Route

• Main Authors: Ho-Pu Lee, 李和璞
• Other Authors: David Chiang
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/8s6tzs

碩士 === 國立臺灣大學 === 商學研究所 === 92 === Due to higher variation of demand existed in supply chain, many approaches are proposed to lower the supply chain cost in a multi-echelon production environment. Among these approaches, alternative route is a popular way applied in the industry to overcome the limitation of capacity and the material supply. Unfortunately, only a few researches related to alternative route are studied. Thus, this thesis intends to look into the issues of alternative route and to develop an efficient mechanism for the industry when this approach is adapted. The production planning problem with alternative route can be formulated as an mixed integer linear programming model intending to minimize the total cost of the supply chain, including the production cost, setup cost, inventory cost and the shortage cost if the orders can’t be delivered on time. In addition to the constraints of limited capacity and supply of raw material, there are complex inter-link relationship existed between each pair of the downstream plants and the upstream plant under the multi-echelon production environment. As the number of customer orders and alternative routes increase, the integer programming model becomes intractable in terms of computation time. Therefore, a generic-algorithm based heuristic method is developed to determine the route for each order initially, followed by a Lagrangain relaxation method and a backward-forward method to obtain the near-optimal production schedules. To evaluate the performance of our heuristic algorithm, over 500 test problems under 25 scenarios are generated from field data. Also, our proposed algorithms are compared to the optimal solution and the results of ILOG CPLEX. We find that the average percentage error is only 0.013% away from the optimum and our algorithm can solve the problem in a very short period of time. Besides, our algorithm is more robust comparing with ILOG CPLEX method. Finally, some implications about when to use the alternative route are suggested.