“Roughly speaking, basic single-solut ion based metaheuristics are more exploitation oriented whereas basic population-based metaheuristics are more exploration oriented.”
Ok, so what’s EXPLOITATION vs EXPLORATION again?–
ok: EXPLOITATION stays within a small area that it thinks might be really good
EXPLORATION doesn’t hang around too long in one area and tries to look at everything.
“A metaheurist ic will be successful on a given optimization problem if it can provide a balance between the exploration
(diversification) and the exploitation (intensification).
Exploitation is needed to identify parts of the search space with high quality solutions. Exploitation is important to intensify the search in some promising areas of the accumulated search experience. “
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So: Single solution examples:
“the simulated annealing method, the tabu search,
the GRASP method, the variable neighborhood search, the guided local search, the iterated local search, and their variants.”
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Section 3 describes the class of metaheurist ics related to population-based metaheurist ics, which manipulate a collection of solutions rather than a single solution at each stage. Section 3.1 describes the field of evolutionary computation and outlines the common search components of this family of algorithms (e.g., selection, variation, and replacemen t). In this subsection, the focus is on evolutionary algorithms such as genetic algorithms, evolution strategie s, evolutionary programming, and genetic programmin g. Section 3.2 presents other evolutionar y algorithms such as estimation of distribution algorithms, differential evolution, coevolution ary algorithms, cultural algorithms and the scatter search and path relinking. Section 3.3 contains an overview of a family of nature inspired algorithms related to Swarm Intelligence. The main algorithms belonging to this field are ant colonies, particle swarm optimization, bacterial foraging, bee colonies, artificial immune systems and biogeography-b ased optimization. Finally, a discussion on the current research status and most promising paths of future research is presented in Section 4
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