Evaluating the performance of various Heuristic Algorithms to Solve Flow Shop Scheduling Problem with Fuzzy Processing Time

This paper evaluates the performance of selected heuristic algorithms, namely Palmer’s and Campbell, Dudek and Smith (CDS) algorithm, Nawaz-Enscore-Ham (NEH), and SAI algorithms for minimizing the makespan in fuzzy flow shop scheduling problem (FSSP) with triangular fuzzy processing times. The algorithms are tested on sixteen benchmark problems with size up to 10 machines and 20 jobs using a MATLAB program. Computational results show that, despite its simplicity, the FNEH algorithm can provide the best results compared to other algorithms, regardless of the size of the problem.

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Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2024-10-25
DOI
https://doi.org/10.30574/wjarr.2024.24.1.3211
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
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article

Evaluating the performance of various Heuristic Algorithms to Solve Flow Shop Scheduling Problem with Fuzzy Processing Time

Sumaia E. Eshim
World Journal of Advanced Research and Reviews
Advanced Manufacturing and Logistics Optimization
article

Evaluating the performance of various Heuristic Algorithms to Solve Flow Shop Scheduling Problem with Fuzzy Processing Time

Sumaia E. Eshim
article en

Abstract

This paper evaluates the performance of selected heuristic algorithms, namely Palmer’s and Campbell, Dudek and Smith (CDS) algorithm, Nawaz-Enscore-Ham (NEH), and SAI algorithms for minimizing the makespan in fuzzy flow shop scheduling problem (FSSP) with triangular fuzzy processing times. The algorithms are tested on sixteen benchmark problems with size up to 10 machines and 20 jobs using a MATLAB program. Computational results show that, despite its simplicity, the FNEH algorithm can provide the best results compared to other algorithms, regardless of the size of the problem.

World Journal of Advanced Research and ReviewsVol. 24(1)
University of Benghazi (LY)
Openalex Percentile: Top 73%
Advanced Manufacturing and Logistics Optimization
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