Multi-objective optimization matching for one-shot multi-attribute exchanges with quantity discounts in E-brokerage

  • Authors:

  • Zhong-Zhong Jiang;W. H. Ip;H. C. W. Lau;Zhi-Ping Fan

  • Affiliations:

  • Department of Management Science and Engineering, School of Business Administration, Northeastern University, Shenyang 110004, China;Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong;School of Management, University of Western Sydney, Sydney, Australia;Department of Management Science and Engineering, School of Business Administration, Northeastern University, Shenyang 110004, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

Quantified Score

Hi-index 12.05

Visualization

Abstract

Electronic brokerages (E-brokerages) are Internet-based organizations that enable buyers and sellers to do business with each other. While E-brokerages have become a significant sector of E-commerce, theory and guidelines for matching the multi-attribute exchange in E-brokerage are sparse. This paper presents an approach to optimize the matching of one-shot multi-attribute exchanges with quantity discounts. Firstly, based on the conception and definition of matching degree and quantity discount, a multi-objective optimization model is proposed to maximize the matching degree and trade volume. This model belongs to a class of multi-objective nonlinear transportation problems and cannot be solved effectively by conventional methods, especially when large-scale problems are involved. Hence, secondly, a novel hybrid multi-objective meta-heuristic algorithm named multi-objective simulated annealing genetic algorithm (MOSAGA) has been developed to solve the proposed model. Finally, the computational results and analyses of some numerical problems are given to illustrate the application and performance of the proposed model and algorithm.