2018
DOI: 10.21817/ijet/2018/v10i6/181006091
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LCMFO: An Improved Moth-Flame Algorithm for Combinatorial Optimization Problems

Abstract: Combinatorial optimization problems (COPs) are challenging class of problems in the field of optimization. Permutations are preferred as solution representation scheme in most cases. Metaheuristic techniques can be used to look for good solutions for COPs with low cost. Moth-flame algorithm (MFO) is one recent population-based metaheuristic technique for continuous optimization problems. In this work improvement of MFO when used to solve COPs is studied. An improved version of MFO (called LCMFO) where Lévy-fli… Show more

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Cited by 4 publications
(7 citation statements)
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“…In order to improve the capabilities of MFO and to overcome the problem of entrapment at local minima/optima in the search space, several variants of the basic MFO algorithm are recently proposed. In this section, the LCMFO [34], EMFO [35], CMFO [36], and CLSGMFO [37] algorithms are reviewed.…”
Section: Variants Of Mfo Algorithmmentioning
confidence: 99%
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“…In order to improve the capabilities of MFO and to overcome the problem of entrapment at local minima/optima in the search space, several variants of the basic MFO algorithm are recently proposed. In this section, the LCMFO [34], EMFO [35], CMFO [36], and CLSGMFO [37] algorithms are reviewed.…”
Section: Variants Of Mfo Algorithmmentioning
confidence: 99%
“…The idea of applying crossover operator within MFO algorithm was firstly proposed by AbdElhamid et al [34]. The authors proposed an improved version of MFO called LCMFO where both Lévy-flight distribution function [47] and crossover function are included in the MFO algorithm.…”
Section: Lcmfomentioning
confidence: 99%
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