An evolutionary algorithmic approach to determine the Nash equilibrium in a duopoly with nonlinearities and constraints
作者：
Highlights：
• The paper presents a novel application of an evolutionary algorithm.
• The paper presents a novel way of determining the Nash equilibrium.
• The approach can be used when analytical or closed-form solutions are not possible.
• It can handle non-linear functions for demand/cost and environmental constraints.
• Results have been validated against solutions obtained analytically.
摘要
•The paper presents a novel application of an evolutionary algorithm.•The paper presents a novel way of determining the Nash equilibrium.•The approach can be used when analytical or closed-form solutions are not possible.•It can handle non-linear functions for demand/cost and environmental constraints.•Results have been validated against solutions obtained analytically.
论文关键词：Nash equilibrium,Evolutionary algorithm,Swarm intelligence,Constrained games,Non-linear payoff functions,NE,Nash Equilibrium,EAA,Evolutionary Algorithmic Approach,BRF,Best Response Function,PR,Promising region,PSO,Particle Swarm Optimization,PSOCP,Particle Swarm Optimization with Composite Particles,GBP,Global Best Position,LBP,Local Best Position
论文评审过程：Received 22 August 2016, Revised 12 December 2016, Accepted 27 December 2016, Available online 28 December 2016, Version of Record 10 January 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.12.037
