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Memetic firefly algorithm for combinatorial optimization

2012/04/23 by Iztok Fister, Fister, Iztok, Yang, Xin-She +1
Computer Science · Decision Sciences · Engineering · #05C15 #05C85 #65K10 #Constraint Satisfaction and Optimization #FOS: Mathematics #Group Theory (math.GR) #Optimization and Control (math.OC) #Scheduling and Timetabling Solutions #Vehicle Routing Optimization Methods

paper · pdf · doi:10.48550/arxiv.1204.5165

openalex publication_date 2012/04/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Firefly algorithms belong to modern meta-heuristic algorithms inspired by nature that can be successfully applied to continuous optimization problems. In this paper, we have been applied the firefly algorithm, hybridized with local search heuristic, to combinatorial optimization problems, where we use graph 3-coloring problems as test benchmarks. The results of the proposed memetic firefly algorithm (MFFA) were compared with the results of the Hybrid Evolutionary Algorithm (HEA), Tabucol, and the evolutionary algorithm with SAW method (EA-SAW) by coloring the suite of medium-scaled random graphs (graphs with 500 vertices) generated using the Culberson random graph generator. The results of firefly algorithm were very promising and showed a potential that this algorithm could successfully be applied in near future to the other combinatorial optimization problems as well.

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