基于拉格朗日松弛和遗传算法的供应链协同计划  

Collaborative planning in supply chains based on Lagrangian relaxation and genetic algorithm

作　　者：聂兰顺[1] 徐晓飞[1] 战德臣[1] 

机构地区：[1]哈尔滨工业大学计算机科学与技术学院,黑龙江哈尔滨150001

出　　处：《计算机集成制造系统》2006年第11期1869-1875,共7页Computer Integrated Manufacturing Systems

基　　金：国家863/CIMS主题资助项目(2003AA4Z3210)。~~

摘　　要：研究了多级供应链伙伴间的生产计划协调优化问题。对集成性多阶段约束生产批量计划模型增加了关联约束和相关需求约束。基于模型的加可分性结构,利用拉格朗日松弛技术将其分解为成员独立的子问题。应用遗传算法更新拉格朗日乘子来协调成员决策,在不干涉成员决策权和私有信息的前提下,实现了多级供应链生产计划的协调优化。仿真实验证明了基于拉格朗日松弛技术与遗传算法的计划协同模式和协调方法的优越性和鲁棒性。Optimization of collaborative planning among partners across various supply chains was studied. Linking constraints and dependent demand constraints were added to the monolithic Multi-Level, multi-item Capacitated Lot Sizing Problem （MLCLSP） model for supply chains. Based on separable structures of the model, MLCLSP was decomposed into facility-separable sub problems by Lagrangian relaxation technology. Genetic algorithm was incorporated into Lagrangian relaxation method to update the Lagrangian multipliers so as to coordinate decentralized decisions of the facilities. The production planning of independent partners could be coordinated and optimized by this framework without interfering their decision authority and private information. Simulation experiments showed that the proposed mechanism and algorithm came close to optimal results as obtained by central coordination in terms of both performance and robustness.

关 键 词：供应链计划 协同计划 拉格朗日松弛 遗传算法 

分 类 号：F406[经济管理—产业经济] O22[理学—运筹学与控制论]