Particle swarm optimization for bi-level pricing problems in supply chains

被引：113

作者：

Gao, Ya ^{[1
]}

Zhang, Guangquan ^{[1
]}

Lu, Jie ^{[1
]}

Wee, Hui-Ming ^{[2
]}

机构：

[1] Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Quantum Computat & Intelligent Syst, Decis Syst & E Serv Intelligence Lab, Sydney, NSW 2007, Australia

[2] Chung Yuan Christian Univ, Dept Ind & Syst Engn, Chungli 32023, Taiwan

来源：

JOURNAL OF GLOBAL OPTIMIZATION | 2011年 / 51卷 / 02期

基金：

澳大利亚研究理事会;

关键词：

Two-stage supply chain; Bi-level programming; Hierarchical decision-making; Optimization; Particle swarm optimization; INVENTORY MODELS;

D O I：

10.1007/s10898-010-9595-8

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

With rapid technological innovation and strong competition in hi-tech industries such as computer and communication organizations, the upstream component price and the downstream product cost usually decline significantly with time. As a result, an effective pricing supply chain model is very important. This paper first establishes two bi-level pricing models for pricing problems with the buyer and the vendor in a supply chain designated as the leader and the follower, respectively. A particle swarm optimization (PSO) based algorithm is developed to solve problems defined by these bi-level pricing models. Experiments illustrate that this PSO based algorithm can achieve a profit increase for buyers or vendors if they are treated as the leaders under some situations, compared with the existing methods.

引用

页码：245 / 254

页数：10

共 29 条

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[Anonymous], 1998, Practical bi-level optimization

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