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A comparative study of Multi-Objective Algorithms for the Assembly Line Balancing and Equipment Selection Problem under consideration of Product Design Alternatives

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Abstract

A realistic and accurate product cost estimation is of high importance during the design phases of products and assembly lines. This paper presents a methodology that aims at supporting decision makers during the design phases of assembly lines by taking into consideration product designs, processes and resources alternatives. First, we introduce a new variant of the Assembly Line Balancing and Equipment Selection Problem, in which Product Design Alternatives are considered. Since the ability to estimate product costs provides grounds for making better decisions, a new detailed cost model whose aim is to translate the complex and interrelated consequences of product design and manufacturing technologies and processes choice into one single cost metric is proposed. In order to solve the problem under study, 34 Multi-Objective Algorithms were developed. The list of developed algorithms includes variants of Evolutionary Algorithms, Ant Colony Optimisation, Artificial Bee Colony, Cuckoo Search Optimisation, Flower Pollination Algorithm, Bat Algorithm and Particle Swarm Optimisation. The performances of all these algorithms are compared based on fifty well-known problem instances in accordance with four multi-objective quality indicators. Finally, the algorithms are ranked using a nonparametric statistical test.

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Notes

  1. The statistical analysis is based on the paper repository of Microsoft Academic, available at following address www.academic.research.microsoft.com/ and by using following keywords: Ant Colony Algorithm, Bee Colony Algorithm, Cuckoo Search Algorithm, Particle Swarm Optimisation, Genetic Algorithm, Line Balancing Problem, Line Design Problem.

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Authors and Affiliations

  1. Fraunhofer Institute for Manufacturing Engineering and Automation - IPA, 70504, Stuttgart, Germany

    Jonathan Oesterle

  2. Charles Delaunay Institute (ICD-LOSI), STMR, UMR CNRS 6281, University of Technology of Troyes, 12 rue Marie Curie, 10010, Troyes, France

    Lionel Amodeo & Farouk Yalaoui

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  1. Jonathan Oesterle
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  2. Lionel Amodeo
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  3. Farouk Yalaoui
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Correspondence to Jonathan Oesterle.

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Oesterle, J., Amodeo, L. & Yalaoui, F. A comparative study of Multi-Objective Algorithms for the Assembly Line Balancing and Equipment Selection Problem under consideration of Product Design Alternatives. J Intell Manuf 30, 1021–1046 (2019). https://doi.org/10.1007/s10845-017-1298-2

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