Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17019
Title: Multi-objective optimization matching for one-shot multi-attribute exchanges with quantity discounts in E-brokerage
Authors: Jiang, ZZ
Ip, WH 
Lau, HCW
Fan, ZP
Keywords: E-brokerage
Genetic algorithm
Multi-attribute exchanges
Multi-objective optimization
Quantity discounts
Simulated annealing
Issue Date: 2011
Publisher: Pergamon Press
Source: Expert systems with applications, 2011, v. 38, no. 4, p. 4169-4180 How to cite?
Journal: Expert systems with applications 
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.
URI: http://hdl.handle.net/10397/17019
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2010.09.079
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