• CN:11-2187/TH
  • ISSN:0577-6686

›› 2005, Vol. 41 ›› Issue (8): 153-158.

• 论文 • 上一篇    下一篇

基于Lagrange松弛分解的多产品生产—分销系统的联合决策

唐加福;Kai-Leung Yung   

  1. 东北大学教育部流程工业综合自动化重点实验室;香港理工大学工业与系统工程系
  • 发布日期:2005-08-15

LAGRANGE RELAXATION DECOMPOSITION BASED JOINT DECISIONS FOR PRODUCTION AND DISTRIBUTION SYSTEM WITH MULTIPLE PRODUCTS

Tang Jiafu;Kai-Leung Yung   

  1. Key Laboratory of Process Industrial Automation of Ministry of Education, Northeastern University Department of Industried and Systems Engineering, The Hong Kong Polytechnic University
  • Published:2005-08-15

摘要: 考虑全球制造环境下多产品生产分销网络系统中的联合物流决策问题,包括供应商指定的生产任务、生产批量、供应商和用户之间的年运输量和订货批量,提出了基于Lagrange松弛的两层分解启发式算法(LRD)来求解联合决策模型(JDM-M),其中第一层是供应商指定的生产任务、生产批量和运输流量的联合决策(APLS-TF),第二层是运输和订货批量的联合决策(TOQ-M)。仿真分析表明LRD对于大规模的集成决策问题是行之有效的方法。

关键词: Lagrange松弛分解, 供应链管理, 联合决策, 启发式, 生产-分销协调

Abstract: The joint decisions of production assignment, lot sizing, transportation and order quantity for multiple products in a production-distribution network with multiple suppliers, multiple products and multiple destinations are discussed. It tries to determine assignment of production among suppliers, production lot size, transportation between suppliers and destinations, and the order quantity at the destinations. A Lagrange relaxation based two-layer decomposition (LRD) method combining several heuristics is developed to solve the joint decision model (JDM-M). The first layer is the joint decisions in assigning production and transportation flow and lot sizing (APLS-TF), and the second layer is the joint transportation and order quantity (TOQ-M) problem. Some simulations show that this LRD with heuristics is effective for solving joint decision problems, particularly for large-scale problem.

Key words: Coordination, Heuristics, Joint decisions, Production and distribution, Two layer

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