Iterated Greedy Algorithms for Combinatorial Optimization: A Systematic Literature Review
Ahmed Missaoui, Cemalettin Öztürk, Barry O’Sullivan · 2023
Metaheuristics are essential tools for efficiently solving combinatorial optimization problems in arising from many fields. As incomplete methods, metaheuristics can provide goodquality results in a very short time. Among these approaches, the Iterated Greedy algorithm (IG) has appeared as a powerful and flexible method for finding near-optimal solutions to combinatorial problems. In this paper, we conducted a comprehensive systematic literature review on the variants of IG approach, and its applications covering the period from its inception in 2007 up to 2022. To the best of our knowledge, this is the first work in which all operators and aspects of IG are discussed to provide a detailed idea about this approach.