Distribution lot-sizing models for arborescent supply chains with discrete-period variable demand
This study formulates a novel mixed-integer programming lot-sizing model for arborescent supply chains with discrete-period variable demand and then develops an efficient two-phase heuristic method, in which a combined multi-period demand ordering policy, rather than the lot-for-lot ordering policy usually assumed in previous papers, is adopted. Two important properties are introduced and used to obtain a better initial feasible solution. The good performance of the proposed heuristic method is verified through a comparison with the optimal solution method. It is also shown that the performance of the proposed combined multi-period demand ordering method is superior to that of the lot-for-lot ordering method. Sensitivity analysis is conducted to explore the impacts of changing the values of relevant parameters on the total supply chain cost, the total number of orders and the total number of opened members. Finally, a well-known logistics company in Taiwan is chosen to demonstrate the excellent performance and the aptness of the proposed ordering method.
Keywords: arborescent supply chains; discrete-period variable demand; distribution lot-sizing models; genetic algorithm
Document Type: Research Article
Affiliations: Department of Industrial Management National Taiwan University of Science and Technology 43 Keelung Road, Section 4 Taipei Taiwan 106 Republic of China, Email: [email protected]
Publication date: 01 October 2004
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