An improved hybrid grey wolf optimization algorithm (IHGWO) is proposed to solve the problem of population diversity, imbalance of exploration and development capabilities, and premature convergence.

Main algorithm that integrates Grey Wolf Optimization (GWO) and Marine Predators Algorithm (MPA) dynamics. initialization.m: Initializes the search agent positions within specified upper and lower ...

This paper analyzes the OBL strategy’s impact on optimizing the GWO algorithm and identifies three shortcomings. the specific limitations of the OBL optimization approach. To address these three ...

Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in ...

This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with strong optimal search ...

The optimization range of the spread coefficient is set to (0, 10). The wolf pack size in the improved gray wolf optimization algorithm is set to 30, and the maximum number of iterations is 400.

The grey wolf optimizer (GWO) algorithm is a metaheuristic technique inspired by the social behavior and hunting strategies of grey wolves. It can be used to solve complex optimization problems in ...

Notifications You must be signed in to change notification settings Grey Wolf Optimization to Minimize Functions with Continuous Variables. The function returns: 1) An array containing the used ...