Metaheuristics
DOI:
https://doi.org/10.30973/inventio/2018.14.34/3Keywords:
heuristics, artificial intelligence, expert systems, combinatorial optimizationAbstract
A brief bibliographic review of the birth of metaheuristics as part of artificial intelligence for the solution of combinatorial optimization problems is presented. Metaheuristics are high-level computational techniques for the approximate resolution of complex problems. The historical foundations of metaheuristics, the main concepts about their operation and their lines of application in real-world problems are described. One of the criteria most used by the scientific community considers the number of solutions explored in each iteration step, which are further divided into two types of metaheuristics: path-based and population-based. The former handle a single solution at each iteration step, while the second handle a set of candidate solutions at each step.
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