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

  • Authors:

  • Ya Gao;Guangquan Zhang;Jie Lu;Hui-Ming Wee

  • Affiliations:

  • Decision Systems & e-Service Intelligence Laboratory, Centre for Quantum Computation & Intelligent Systems, Faculty of Engineering & Information Technology, University of Technology, Sydney, Austr ...;Decision Systems & e-Service Intelligence Laboratory, Centre for Quantum Computation & Intelligent Systems, Faculty of Engineering & Information Technology, University of Technology, Sydney, Austr ...;Decision Systems & e-Service Intelligence Laboratory, Centre for Quantum Computation & Intelligent Systems, Faculty of Engineering & Information Technology, University of Technology, Sydney, Austr ...;Department of Industrial and Systems Engineering, Chung Yuan Christian University, Chungli, Taiwan, ROC 32023

  • Venue:
  • Journal of Global Optimization
  • Year:
  • 2011

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Abstract

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.