A Social Spider Optimization Algorithm for Hybrid Flow Shop Scheduling with Multiprocessor Task

7 Pages Posted: 20 Dec 2018

See all articles by Mohamed Kurdi

Mohamed Kurdi

Aydın Adnan Menderes University

Date Written: December 15, 2018

Abstract

Hybrid flow shop scheduling with multiprocessor task (HFSPMT) is a strongly NP-hard problem that has a wide range of applications in several real-life industrial environments. Due to its essential complexity and practical relevance, HFSPMT has been of an increasing interest for researchers and industrialists in the last two decades. Social spider optimization (SSO) is a recent swarm intelligence algorithm that has been rarely applied on combinatorial optimization problems. In order to make a small step toward having an idea about its effectiveness in solving combinatorial optimization, in this work, a new SSO algorithm is proposed to solve HFSPMT problem with the objective of makespan minimization. The proposed algorithm is experimented on benchmark instances and compared with other existing swarm intelligence algorithms in the literature. The obtained results and the comparisons show that the performance of the proposed algorithm is highly competitive in terms of solution quality.

Suggested Citation

Kurdi, Mohamed, A Social Spider Optimization Algorithm for Hybrid Flow Shop Scheduling with Multiprocessor Task (December 15, 2018). 12th International NCM Conference: Challenges in Industrial Engineering & Operation Management . Available at SSRN: https://ssrn.com/abstract=3301792 or http://dx.doi.org/10.2139/ssrn.3301792

Mohamed Kurdi (Contact Author)

Aydın Adnan Menderes University

Kepez Mevkii
Efeler/Aydın
Turkey

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