引用本文:曾宇容,万建超,吕盛祥,等.联合补货策略下的供应商选择和订货量分配协同优化[J].控制与决策,2019,34(8):1714-1722
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联合补货策略下的供应商选择和订货量分配协同优化
曾宇容1,2, 万建超3, 吕盛祥2, 王思睿2, 王林2
(1. 湖北经济学院信息与通信工程学院,武汉430205;2. 华中科技大学管理学院,武汉430074;3. 普天信息技术有限公司,北京100080)
摘要:
分析基于联合补货策略的供应商选择与商品订货量分配协同决策问题,设计一种有效的改进差分进化算法(Improved differential evolution,IDE)进行求解.在考虑商品异质性带来的分组约束基础上,构建一种拓展的供应商选择与订货量分配协同决策新模型.对比算例分析表明,IDE在求解此问题及其扩展问题时优于标准差分进化算法和模拟退火算法,随机生成的大规模算例进一步验证了IDE求解此类复杂问题的优越性.
关键词:  供应商选择  订货量分配  联合补货  分组约束  差分进化算法  模拟退火算法
DOI:10.13195/j.kzyjc.2018.0003
分类号:TP273
基金项目:湖北省教育厅重点科研项目(D20152203).
Collaborative optimization of suppliers selection and order quantity allocation using joint replenishment policy
ZENG Yu-rong1,2,WAN Jian-chao3,LYU Sheng-xiang2,WANG Si-rui2,WANG Lin2
(1. School of Communication and Information Engineering,Hubei University of Economics,Wuhan430205,China;2. School of Management,Huazhong University of Science and Technology,Wuhan430074,China;3. Potevio Information Technology Co. Ltd., Beijing100080,China)
Abstract:
The problem of coordinated supplier selection and quantity allocation based on the joint replenishment policy is studied, and an effective and improved differential evolution (IDE) algorithm is proposed to solve the problem. Then a new coordinated supplier selection and order quantity allocation model considering grouping constraint caused by the heterogeneity of items is developed. Results of contrastive numeric examples show that the IDE algorithm outperforms the standard DE algorithm and the simulated annealing(SA) algorithm in solving this problem and its extension type. The effectiveness of the IDE algorithm is further verified by randomly generated large-scale numerical examples.
Key words:  supplier selection  order quantity allocation  joint replenishment  grouping constraint  differential evolution algorithm  simulated annealing

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