A Novel Particle Swarm Optimization Approach to Support Decision-Making in the Multi-Round of an Auction by Game Theory

• Main Authors: Trinh Ngoc Bao, Quyet-Thang Huynh, Xuan-Thang Nguyen, Gia Nhu Nguyen, Dac-Nhuong Le
• Format: Article
• Language: English
• Published: Atlantis Press 2020-09-01
• Series: International Journal of Computational Intelligence Systems
• Subjects: Multi-round procurement; Project conflicts; Game theory; Particle swarm optimization; Nash equilibrium; Decision support system
• Online Access: https://www.atlantis-press.com/article/125944527/view

In this paper, game-theoretic optimization by particle swarm optimization (PSO) is used to determine the Nash equilibrium value, in order to resolve the confusion in choosing appropriate bidders in multi-round procurement. To this end, we introduce an approach that proposes (i) a game-theoretic model of the multi-round procurement problem; (ii) a Nash equilibrium strategy corresponding to the multi-round strategy bid; and (iii) an application of PSO for the determination of the global Nash equilibrium point. The balance point in Nash equilibrium can help to maintain a sustainable structure, not only in terms of project management but also in terms of future cooperation. As an alternative to procuring entities subjectively, a methodology using Nash equilibrium to support decision-making is developed to create a balance point that benefits procurement in which buyers and suppliers need multiple rounds of bidding. To solve complex optimization problems like this, PSO has been found to be one of the most effective meta-heuristic algorithms. These results propose a sustainable optimization procedure for the question of how to choose bidders and ensure a win-win relationship for all participants involved in the multi-round procurement process.