Open Access

ARTICLE

Optimizing Bidders Selection of Multi-Round Procurement Problem in Software Project Management Using Parallel Max-Min Ant System Algorithm

Dac-Nhuong Le^1,2,3,*, Gia Nhu Nguyen^2,4, Harish Garg⁵, Quyet-Thang Huynh⁶, Trinh Ngoc Bao⁷, Nguyen Ngoc Tuan⁸

1 Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam
2 Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Vietnam
3 Faculty of Information Technology, Haiphong University, Haiphong, 180000, Vietnam
4 Graduate School, Duy Tan University, Da Nang, 550000, Vietnam
5 School of Mathematics, Thapar Institute of Engineering and Technology, Patiala, 147004, India
6 Hanoi University of Science and Technology, Hanoi, 100000, Vietnam
7 Hanoi University, Hanoi, 100000, Vietnam
8 Department of ICT, Ministry of Education and Training, Hanoi, 100000, Vietnam

* Corresponding Author: Dac-Nhuong Le. Email:

(This article belongs to the Special Issue: Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)

Computers, Materials & Continua 2021, 66(1), 993-1010. https://doi.org/10.32604/cmc.2020.012464

Received 03 June 2020; Accepted 25 July 2020; Issue published 30 October 2020

Abstract

This paper presents a Game-theoretic optimization via Parallel MinMax Ant System (PMMAS) algorithm is used in practice to determine the Nash equilibrium value to resolve the confusion in choosing appropriate bidders of multi-round procurement problem in software project management. To this end, we introduce an approach that proposes: (i) A Game-theoretic model of multiround procurement problem (ii) A Nash equilibrium strategy corresponds to multi-round strategy bid (iii) An application of PSO for the determination of global Nash equilibrium. 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 of procuring entities subjectively, a methodology to support decision making has been studied using Nash equilibrium to create a balance point on benefit in procurement where buyers and suppliers need multiple rounds of bidding. Our goal focus on the balance point in Nash Equilibrium to optimizing bidder selection in multi-round procurement which is the most beneficial for both investors and selected tenderers. Our PMMAS algorithm is implemented based on MPI (message passing interface) to find the approximate optimal solution for the question of how to choose bidders and ensure a path for a win-win relationship of all participants in the procurement process. We also evaluate the speedup ratio and parallel efficiency between our algorithm and other proposed algorithms. As the experiment results, the high feasibility and effectiveness of the PMMAS algorithm are verified.

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Citations