Solving linear Programming Problems Using The Grey Wolf Optimizer in R

Abstract

This paper presents the Grey Wolf Optimizer (GWO), a metaheuristic algorithm inspired by the leadership hierarchy and cooperative hunting strategies of grey wolves, as an approach for solving linear programming models. The algorithm was implemented in R language using advanced programming techniques and the functions available in the MetaheuristicOPT library. Several linear programming problems were tested, and the proposed algorithm successfully obtained optimal solutions. The performance of GWO was compared with the classical Simplex method, Genetic Algorithms, and TORA Software. Results indicate that GWO is efficient and can be used  effectively for solving such problems in operations research applications.