Classifying Metaheuristics: Towards a unified multi-level classification system

Abstract

Metaheuristics provide the means to approximately solve complex optimisation problems when exact optimisers cannot be utilised. This led to an explosion in the number of novel metaheuristics, most of them metaphor-based, using nature as a source of inspiration. Thus, keeping track of their capabilities and innovative components is an increasingly difficult task. This can be resolved by an exhaustive classification system. Trying to classify metaheuristics is common in research, but no consensus on a classification system and the necessary criteria has been established so far. Furthermore, a proposed classification system can not be deemed complete if inherently different metaheuristics are assigned to the same class by the system. In this paper we provide the basis for a new comprehensive classification system for metaheuristics. We first summarise and discuss previous classification attempts and the utilised criteria. Then we present a multi-level architecture and suitable criteria for the task of classifying metaheuristics. A classification system of this kind can solve three main problems when applied to metaheuristics: organise the huge set of existing metaheuristics, clarify the innovation in novel metaheuristics and identify metaheuristics suitable to solve specific optimisation tasks.

Combinatorial Optimization Problems and Metaheuristics: Review, Challenges, Design, and Development

“…The performance of a solution in each criterion is not enough, and an analysis that considers all criteria together must support this process. Moreover, the objectives may potentially conflict and concur with each other [19,24,[40][41][42]46,47]. Thus, MOCOPs require additional efforts to assess, compare, and determine which solution performs better than others, balancing multiple criteria.…”

“…The classification of metaheuristics is a fuzzy and debatable topic. There are various ways and distinct dimensions to classify the metaheuristics [12,15,19,53,57,[60][61][62]. Some researchers generally choose the most appropriate classification criteria according to their point of view or work [12,19,62].…”

“…There are various ways and distinct dimensions to classify the metaheuristics [12,15,19,53,57,[60][61][62]. Some researchers generally choose the most appropriate classification criteria according to their point of view or work [12,19,62]. This issue will be better explained in Section 3.1, Lack of Guidelines, to organize the field.…”

“…Furthermore, the classification of algorithms from a source of inspiration is a fuzzy topic in the literature [6,12,15,19,20]. It is common to find divergent points of view to classify them according to the inspiration applied.…”

“…Nevertheless, a determined metaheuristic cannot have a great performance in all categories of optimization problems because its approach may not work well in several other problems, a hypothesis already proved by "No Free Lunch" theorems [14,15,[17][18][19]. These points have "engaged" the research community to develop a vast number of metaheuristics [6,15,19].…”