Nash equilibrium sorting genetic algorithm for simultaneous competitive maximal covering location with multiple players

In this article, a new genetic algorithm (GA), called the Nash equilibrium sorting (NESGA,) is introduced to identify equilibria for competitive maximal covering location problem with two and three competitors, which combinatorial game theory where it computationally intractable enumerate all decision options of competitors. Although GAs are widely used in optimization, their applications non-cooperative, simultaneous games have been limited owing challenges guiding evolutionary search equilibria, not necessarily on Pareto front space cannot be found by current multi-objective GAs. A novel fitness assignment strategy proposed help NESGA converge multiple equilibria. Computational experiments show that can discover single run outperform other game-theoretic