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Soft Computing

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26.02.2018 | Focus

Solving permutation flow-shop scheduling problem by rhinoceros search algorithm

verfasst von: Suash Deb, Zhonghuan Tian, Simon Fong, Rui Tang, Raymond Wong, Nilanjan Dey

Erschienen in: Soft Computing | Ausgabe 18/2018

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Abstract

In this paper, a novel meta-heuristic search algorithm inspired by rhinoceros’ natural behaviour is proposed, namely rhinoceros search algorithm (RSA). Similar to our earlier version called elephant search algorithm, RSA simplifies certain habitual characteristics of rhinoceros and stream-lines the search operations, thereby reducing the number of operational parameters required to configure the model. Via computer simulation, it is shown that RSA is able to outperform certain classical meta-heuristic algorithms. Different dimensions of optimization problems are tested, and good results are observed by RSA. The RSA is also implemented on permutation flow-shop scheduling problem (PFSP) with some representation method. Four different problem scales are used. Compared with partible swarm optimization (PSO) on PFSP, the RSA outperforms PSO on different problem scales with a 3% improvement.

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Titel: Solving permutation flow-shop scheduling problem by rhinoceros search algorithm
verfasst von: Suash Deb
Zhonghuan Tian
Simon Fong
Rui Tang
Raymond Wong
Nilanjan Dey
Publikationsdatum: 26.02.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 18/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3075-3

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