Initialization of metaheuristics: comprehensive review, critical analysis, and research directions

Initialization of metaheuristics is a crucial topic that lacks a comprehensive and systematic review of the state of the art. Providing such a review requires in-depth study and knowledge of the advances and challenges in the broader field of metaheuristics, especially with regard to diversification strategies, in order to assess the proposed methods and provide insights for initialization. Motivated by the aforementioned research gap, we provide a related review and begin by describing the main metaheuristic methods and their diversification mechanisms. Then, we review and analyze the existing initialization approaches while proposing a new categorization of them. Next, we focus on challenging optimization problems, namely constrained and discrete optimization. Lastly, we give insights on the initialization of local search approaches.

Automated summary

This article discusses the importance of initialization in metaheuristics and highlights the lack of comprehensive reviews in the field. It provides a new review, covering the main metaheuristic methods, diversification mechanisms, challenging optimization problems, and the initialization of local search methods.