Iterated Greedy Algorithms for Combinatorial Optimization: A Systematic Literature Review

被引：0
|
作者：
Missaoui, Ahmed [1 ]
Ozturk, Cemalettin [2 ]
O'Sullivan, Barry [1 ]
机构：
[1] Univ Coll Cork, Sch Comp Sci & IT, Insight Ctr Data Analyt, Cork, Ireland
[2] Munster Technol Univ, Proc Energy Transport Engn, Cork, Ireland
来源：
2023 20TH ACS/IEEE INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS, AICCSA | 2023年
基金：
爱尔兰科学基金会;
关键词：
Iterated Greedy; Destruction-reconstruction; Optimization; Meta-heuristics; Systematic Literature; TARDINESS MINIMIZATION; MINIMIZING MAKESPAN; SCHEDULING PROBLEM; SEARCH ALGORITHM; FLOWSHOP; MACHINE; FLOWTIME;
D O I：
10.1109/AICCSA59173.2023.10479246
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Metaheuristics are essential tools for efficiently solving combinatorial optimization problems in arising from many fields. As incomplete methods, metaheuristics can provide good-quality 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.
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页数：7
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