Abstract
In recent years, many researchers have utilized metaheuristic optimization algorithms along with fuzzy logic theory in their studies for various purposes. The harmony search (HS) algorithm is one of the metaheuristic optimization algorithms that is widely employed in different studies along with fuzzy logic (FL) theory. FL theory is a mathematical approach to expressing uncertainty by applying the conceptualization of fuzziness in a system. This review paper presents an extensive review of published papers based on the combination of HS and FL systems. In this regard, the functional characteristics of models obtained from integration of FL and HS have been reported in various articles, and the performance of each study is investigated. The basic concept of the FL approach and its derived models are introduced to familiarize readers with the principal mechanisms of FL models. Moreover, appropriate descriptions of the primary classifications acquired from the coexistence of FL and HS methods for specific purposes are reviewed. The results show that the high efficiency of HS to improve the exploration of FL in achieving the optimal solution on the one hand, and the capability of fuzzy inference systems to provide more flexible and dynamic adaptation of the HS parameters based on human perception on the other hand, can be a powerful combination for solving optimization problems. This review paper is believed to be a useful resource for students, engineers, and professionals.
Highlights
The complex nature of many engineering problems on the one hand and the problem of dealing with the concept of uncertainty in such problems on the other hand has led researchers to utilize metaheuristic optimization algorithms and fuzzy logic (FL) theory in solving real life optimization problems
Ability, and effective qualities of the harmony search (HS) among optimization algorithms and an interesting definition of FL, the distinguishing combinations of the HS and FL in terms of the type of connection were introduced in the literature
It is seen that different variants of the HS in terms of implementations, improvements, multi-objective variants, hybridizations, and various FL models were included in a full reference list
Summary
The complex nature of many engineering problems on the one hand and the problem of dealing with the concept of uncertainty in such problems on the other hand has led researchers to utilize metaheuristic optimization algorithms and fuzzy logic (FL) theory in solving real life optimization problems. FL is a mathematical approach to expressing uncertainty that helps in fuzziness conceptualization in a system to a measurable parameter. In this regard, the HS algorithm along with FL have been investigated in numerous research papers with different goals. The HS algorithm aims to simulate attempts by the players to improve harmonies. In a large number of test trials, these primary benefits resulted in the substantial use of the HS algorithm compared with other methodologies for optimization [3]
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