Simulation-Based Comparison of P-Metaheuristics for FJSP with and Without Fuzzy Processing Time

The population based metaheuristic (P-metaheuristic) is a stochastic algorithm for optimization. This paper presents five different P-metaheuristics (BAT, Firefly, Cuckoo search, basic Particle swarm optimization (BPSO) and a modified PSO (M-PSO)) for solving Flexible Job Shop Problem with and witho...

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Bibliographic Details
Published inRecent Trends and Future Technology in Applied Intelligence Vol. 10868; pp. 408 - 413
Main Authors Rim, Zarrouk, Imed, Bennour, Abderrazek, Jemai
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2018
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Flexible job shop scheduling problem
Fuzzy processing time
Particle swarm optimization
Population based metaheuristics
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Summary:The population based metaheuristic (P-metaheuristic) is a stochastic algorithm for optimization. This paper presents five different P-metaheuristics (BAT, Firefly, Cuckoo search, basic Particle swarm optimization (BPSO) and a modified PSO (M-PSO)) for solving Flexible Job Shop Problem with and without fuzzy processing time (FJSP/fFJSP). We intend to evaluate and compare the performance of these different algorithms by using thirteen benchmarks for FJSP and four benchmarks for fFJSP. The results demonstrate the superiority of the M-PSO algorithm over the other techniques to solve both FJSP and fFJSP.
ISBN:331992057X
9783319920573
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-92058-0_39