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《工程管理前沿(英文)》 >> 2018年 第5卷 第4期 doi: 10.15302/J-FEM-2018059

Product decomposition strategy for optimization of supply chain planning

Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh 15289, USA

录用日期 : 2018-11-12 发布日期 :2018-11-29

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摘要

Optimization of large-scale supply chain planning models requires the application of decomposition strategies to reduce the computational expense. Two major options are to use either spatial or temporal Lagrangean decomposition. In this paper, to further reduce the computational expense a novel decomposition scheme by products is presented. The decomposition is based on a reformulation of knapsack constraints in the problem. The new approach allows for simultaneous decomposition by products and by time periods, enabling the generation of a large number of subproblems, that can be solved by using parallel computing. The case study shows that the proposed product decomposition exhibits similar performance as the temporal decomposition, and that selecting different orders of products and aggregating the linking constraints can improve the efficiency of the algorithm.

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