DocumentCode :
3572433
Title :
An improved particle swarm optimization algorithm for winner determination in multi-attribute combinatorial reverse auction
Author :
Xiaohu Qian ; Min Huang ; Jun Tu ; Xingwei Wang
Author_Institution :
State Key Lab. of Synthetical Autom. for Process Ind., Northeastern Univ., Shenyang, China
fYear :
2014
Firstpage :
605
Lastpage :
609
Abstract :
An electronic reverse auction system with one buyer and multiple suppliers is considered in this paper. The buyer procures multi-items from potential suppliers with unconstrained capacity and the suppliers bid competitively on combinations of items in the system. As an important decision problem from the buyer´s perspective, a winner determination problem (WDP) of multi-items single-unit combinatorial reverse auction with multi-attributes of each item is described and a bi-objective programming model that minimizes the total procurement cost and maximizes the total score of the winning suppliers based on multi-attributes of each item is established. According to the characteristics of the model, an equivalent single-objective programming model is obtained. However, as the problem is NP-hard, an improved particle swarm optimization (IPSO) algorithm embedded with the quantum-inspired evolutionary and the asynchronous time-varying learning strategies is proposed. Also, a heuristic search algorithm is applied to repair the infeasible solutions in the process of IPSO. Experimental results show the effectiveness of the improved algorithm.
Keywords :
combinatorial mathematics; computational complexity; cost reduction; electronic commerce; evolutionary computation; particle swarm optimisation; search problems; IPSO algorithm; NP-hard problem; WDP; asynchronous time-varying learning strategy; bi-objective programming model; decision problem; electronic reverse auction system; equivalent single-objective programming model; heuristic search algorithm; improved particle swarm optimization algorithm; multiattribute combinatorial reverse auction; multiitems single-unit combinatorial reverse auction; quantum-inspired evolutionary; total procurement cost minimization; winner determination problem; winning suppliers; Algorithm design and analysis; Equations; Heuristic algorithms; Mathematical model; Numerical models; Particle swarm optimization; Procurement; heuristic search; improved particle swarm optimization (IPSO); multi-attribute combinatorial reverse auction; winner determination;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
Type :
conf
DOI :
10.1109/WCICA.2014.7052783
Filename :
7052783
Link To Document :
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