Economics at your fingertips  

An Intelligent Algorithm for Solving the Efficient Nash Equilibrium of a Single-Leader Multi-Follower Game

Lu-Ping Liu () and Wen-Sheng Jia ()
Additional contact information
Lu-Ping Liu: School of Mathematics and Statistic, Guizhou University, Huaxidadao, Guiyang 550025, China
Wen-Sheng Jia: School of Mathematics and Statistic, Guizhou University, Huaxidadao, Guiyang 550025, China

Mathematics, 2021, vol. 9, issue 5, 1-14

Abstract: This aim of this paper is to provide the immune particle swarm optimization (IPSO) algorithm for solving the single-leader–multi-follower game (SLMFG). Through cooperating with the particle swarm optimization (PSO) algorithm and an immune memory mechanism, the IPSO algorithm is designed. Furthermore, we define the efficient Nash equilibrium from the perspective of mathematical economics, which maximizes social welfare and further refines the number of Nash equilibria. In the end, numerical experiments show that the IPSO algorithm has fast convergence speed and high effectiveness.

Keywords: single-leader–multi-follower game; immune particle swarm optimization (IPSO) algorithm; probability density selection function; efficient Nash equilibrium (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf) (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Mathematics is currently edited by Ms. Patty Hu

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

Page updated 2022-03-26
Handle: RePEc:gam:jmathe:v:9:y:2021:i:5:p:454-:d:504755