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 algorithms and …

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 three …

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 given problem.

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 problems makes them …

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