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Arsalan Rahmani

Arsalan Rahmani

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 55881268200
Faculty: Faculty of Science
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Research

Title
A hybrid Firefly-Genetic Algorithm for the capacitated facility location problem
Type
JournalPaper
Keywords
Firefly algorithm Genetic algorithm Capacitated facility location problem Meta-heuristic
Year
2014
Journal INFORMATION SCIENCES
DOI
Researchers Arsalan Rahmani ، seyed ali mirhassani

Abstract

Capacitated facility location problem (CFLP) is a well-known combinatorial optimization problem with applications in distribution and production planning that is classified as an NP-Hard problem. The aim is to determine where to locate facilities and how to move commodities such that the customers’ demands are satisfied and the total cost minimized. In this paper, a new hybrid optimization method called Hybrid Evolutionary Firefly-Genetic Algorithm is proposed, which is inspired by social behavior of fireflies and the phenomenon of bioluminescent communication. The method combines the discrete Firefly Algorithm (FA) with the standard Genetic Algorithm (GA). It is devoted to the detailed description of the problem, and an adaption of the algorithm. Computational results on random generated problems consisting of 2000 locations and 2000 customers are reported.