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DOI: 10.14569/IJACSA.2017.081256
PDF

A Firefly Algorithm for the Mono-Processors Hybrid Flow Shop Problem

Author 1: Latifa DEKHICI
Author 2: Khaled BELKADI

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 12, 2017.

  • Abstract and Keywords
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Abstract: Nature-inspired swarm metaheuristics become one of the most powerful methods for optimization. In discrete optimization, the efficiency of an algorithm depends on how it is adapted to the problem. This paper aims to provide a discretization of the Firefly Algorithm (FF) for the scheduling of a specific manufacturing system, which is the mono processors two-stage hybrid flow shop (HFS). This kind of manufacturing system appears in several fields as the operating theatre scheduling problem. Results of proposed discrete firefly algorithm are compared to results of other methods found in the literature. Computational results with different numbers of fireflies and on a standard HFS benchmark of about 55 cases, generating about 1900 instances demonstrates that the proposed discretized metaheuristic reaches the best makespan.

Keywords: Firefly algorithm; hybrid flow shop; metaheuristics; discrete optimization

Latifa DEKHICI and Khaled BELKADI, “A Firefly Algorithm for the Mono-Processors Hybrid Flow Shop Problem” International Journal of Advanced Computer Science and Applications(IJACSA), 8(12), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081256

@article{DEKHICI2017,
title = {A Firefly Algorithm for the Mono-Processors Hybrid Flow Shop Problem},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081256},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081256},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {12},
author = {Latifa DEKHICI and Khaled BELKADI}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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