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

Authors

Trinh Ngoc Bao¹, Quyet-Thang Huynh^2, , Xuan-Thang Nguyen^1, , Gia Nhu Nguyen^{3, 4,} , Dac-Nhuong Le^{4, 5, 6, *,}

¹Hanoi University, Hanoi 100000, Vietnam

²Hanoi University of Science and Technology, Hanoi 100000, Vietnam

³Graduate School, Duy Tan University, Da Nang 550000, Vietnam

⁴Faculty of Information Technology, Duy Tan University, Da Nang 550000, Vietnam

⁵Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam

⁶Faculty of Information Technology, Haiphong University, Haiphong 180000, Vietnam

^*Corresponding author. Email: ledacnhuong@duytan.edu.vn

DOI

10.2991/ijcis.d.200828.002How to use a DOI?

Keywords

Multi-round procurement; Project conflicts; Game theory; Particle swarm optimization; Nash equilibrium; Decision support system; Multi-objective

Abstract

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.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Trinh Ngoc Bao
AU  - Quyet-Thang Huynh
AU  - Xuan-Thang Nguyen
AU  - Gia Nhu Nguyen
AU  - Dac-Nhuong Le
PY  - 2020
DA  - 2020/09/14
TI  - A Novel Particle Swarm Optimization Approach to Support Decision-Making in the Multi-Round of an Auction by Game Theory
JO  - International Journal of Computational Intelligence Systems
SP  - 1447
EP  - 1463
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200828.002
DO  - 10.2991/ijcis.d.200828.002
ID  - Bao2020
ER  -