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Choosing efficient meta-heuristics to solve the assembly line balancing problem: A landscape analysis approach
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-6280-1848
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-5530-3517
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-0111-1776
2019 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 81, p. 1248-1253Article in journal (Refereed) Published
Abstract [en]

It is widely known that the assembly line balancing problem (ALBP) is an NP-hard optimization problem. Although different meta-heuristics have been proposed for solving this problem so far, there is no convincing support that what type of algorithms can perform more efficiently than the others. Thus, using some statistical measures, the landscape of the simple ALBP is studied for the first time in the literature. The results indicate a flat landscape for the problem where the local optima are uniformly scattered over the search space. Accordingly, the efficiency of population-based algorithms in addressing the considered problem is statistically validated.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 81, p. 1248-1253
Keywords [en]
Assembly line balancing, fitness landscape analysis, meta-heuristic algorithms
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-17280DOI: 10.1016/j.procir.2019.03.302Scopus ID: 2-s2.0-85068480053OAI: oai:DiVA.org:his-17280DiVA, id: diva2:1329812
Conference
52nd CIRP Conference on Manufacturing Systems, Ljubljana, Slovenia, June 12-14, 2019
Projects
This study is supported by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 723711 through the MANUWORK project
Funder
EU, Horizon 2020, 723711Available from: 2019-06-24 Created: 2019-06-24 Last updated: 2019-08-19Bibliographically approved

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Nourmohammadi, AmirFathi, MasoodNg, Amos H. C.

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