A New Hybrid Social Spider Optimization and Tabu Search for the Permutation Flow Shop Scheduling Problem.
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| Title: | A New Hybrid Social Spider Optimization and Tabu Search for the Permutation Flow Shop Scheduling Problem. |
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| Authors: | Kurdi, Mohamed1,2 (AUTHOR) mohamed_kurdi@idlib.edu.sy, Mzili, Toufik3 (AUTHOR), Steef, Ahmad1,2 (AUTHOR), Shaheen, Momina4 (AUTHOR), Al-Quraan, Ayman (AUTHOR) aymanqran@yu.edu.jo |
| Source: | Journal of Electrical & Computer Engineering. 3/12/2026, Vol. 2026, p1-14. 14p. |
| Subjects: | Flow shop scheduling, Tabu search algorithm, Combinatorial optimization, Production scheduling, Benchmark problems (Computer science), Metaheuristic algorithms |
| Abstract: | The permutation flow shop scheduling problem (PFSP) is an NP‐complete problem that represents a significant challenge in manufacturing and production environments. Memetic algorithms (MAs) that hybridize global search strategies with local refinement techniques are widely regarded as among the most powerful metaheuristic approaches for addressing complex combinatorial challenges. This paper presents a new hybrid social spider optimization and tabu search (SSO‐TS) approach for minimizing the makespan in PFSP. SSO‐TS combines the strengths of SSO and TS by unifying the global diversification capability of SSO with the local intensification capability of TS, yielding a hybrid strategy that achieves a balance between diversification and intensification. The performance of SSO‐TS is evaluated on the established Taillard benchmark suite. To assess the impact of hybridization, SSO‐TS is first compared with the original SSO algorithm. The results demonstrate that hybridizing SSO with TS significantly improves performance, achieving a 77% reduction in the average percentage error of the best‐obtained solution. SSO‐TS is then evaluated against four leading algorithms from previous research. The experimental results indicate that SSO‐TS outperforms three of the four with respect to solution quality. These findings validate the effectiveness of the proposed approach and establish SSO‐TS as an effective and competitive approach for solving the PFSP. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Electrical & Computer Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 192288661 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A New Hybrid Social Spider Optimization and Tabu Search for the Permutation Flow Shop Scheduling Problem. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kurdi%2C+Mohamed%22">Kurdi, Mohamed</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> mohamed_kurdi@idlib.edu.sy</i><br /><searchLink fieldCode="AR" term="%22Mzili%2C+Toufik%22">Mzili, Toufik</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Steef%2C+Ahmad%22">Steef, Ahmad</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shaheen%2C+Momina%22">Shaheen, Momina</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Al-Quraan%2C+Ayman%22">Al-Quraan, Ayman</searchLink> (AUTHOR)<i> aymanqran@yu.edu.jo</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Electrical+%26+Computer+Engineering%22">Journal of Electrical & Computer Engineering</searchLink>. 3/12/2026, Vol. 2026, p1-14. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Flow+shop+scheduling%22">Flow shop scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Tabu+search+algorithm%22">Tabu search algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Combinatorial+optimization%22">Combinatorial optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Production+scheduling%22">Production scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Benchmark+problems+%28Computer+science%29%22">Benchmark problems (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The permutation flow shop scheduling problem (PFSP) is an NP‐complete problem that represents a significant challenge in manufacturing and production environments. Memetic algorithms (MAs) that hybridize global search strategies with local refinement techniques are widely regarded as among the most powerful metaheuristic approaches for addressing complex combinatorial challenges. This paper presents a new hybrid social spider optimization and tabu search (SSO‐TS) approach for minimizing the makespan in PFSP. SSO‐TS combines the strengths of SSO and TS by unifying the global diversification capability of SSO with the local intensification capability of TS, yielding a hybrid strategy that achieves a balance between diversification and intensification. The performance of SSO‐TS is evaluated on the established Taillard benchmark suite. To assess the impact of hybridization, SSO‐TS is first compared with the original SSO algorithm. The results demonstrate that hybridizing SSO with TS significantly improves performance, achieving a 77% reduction in the average percentage error of the best‐obtained solution. SSO‐TS is then evaluated against four leading algorithms from previous research. The experimental results indicate that SSO‐TS outperforms three of the four with respect to solution quality. These findings validate the effectiveness of the proposed approach and establish SSO‐TS as an effective and competitive approach for solving the PFSP. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Electrical & Computer Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/jece/6022369 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1 Subjects: – SubjectFull: Flow shop scheduling Type: general – SubjectFull: Tabu search algorithm Type: general – SubjectFull: Combinatorial optimization Type: general – SubjectFull: Production scheduling Type: general – SubjectFull: Benchmark problems (Computer science) Type: general – SubjectFull: Metaheuristic algorithms Type: general Titles: – TitleFull: A New Hybrid Social Spider Optimization and Tabu Search for the Permutation Flow Shop Scheduling Problem. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kurdi, Mohamed – PersonEntity: Name: NameFull: Mzili, Toufik – PersonEntity: Name: NameFull: Steef, Ahmad – PersonEntity: Name: NameFull: Shaheen, Momina – PersonEntity: Name: NameFull: Al-Quraan, Ayman IsPartOfRelationships: – BibEntity: Dates: – D: 12 M: 03 Text: 3/12/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20900147 Numbering: – Type: volume Value: 2026 Titles: – TitleFull: Journal of Electrical & Computer Engineering Type: main |
| ResultId | 1 |
