Metaheuristics is a rather unfortunate1 term often used to describe a major subfield, indeed the primary subfield, of stochastic optimization. Stochastic optimization is the general class of …

A metaheuristic method is particularly relevant in the context of solving search and optimization problems. It describes a method that uses one or more heuristics and therefore inherits all the …

Roughly speaking, metaheuristic is considered to be an algorithmic structure that generally applied to a variety of optimization problems with only a few modifications for adapting to the …

Metaheuristic algorithms attempt to find the best (feasible) solution out of all possible solutions of an optimization problem. To this end, they evaluate potential solutions and perform a series of …

Oct 7, 2024 · To this end, we introduce a step by step methodology covering every research phase that should be followed when addressing this scientific field.

Metaheuristic algorithms offer a versatile and effective approach for solving large-scale optimization problems. Their ability to handle complex, nonlinear and high-dimensional …

The book first identifies the importance of metaheuristic algorithm research and describes its emergence and development. In addition, various application scenarios for metaheuristic …