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Distribution lot-sizing models for arborescent supply chains with discrete-period variable demand
Authors:Huan Neng Chiu  Yi Shyang Lee  Chun Yen Tseng
Affiliation:Department of Industrial Management , National Taiwan University of Science and Technology , 43 Keelung Road, Section 4, Taipei, Taiwan 106, Republic of China E-mail: hnchiu@im.ntust.edu.tw
Abstract:
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  distribution lot-sizing models  discrete-period variable demand  genetic algorithm
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