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European Conference on Genetic Programming (Part of EvoStar)

EuroGP 2021: Genetic Programming pp 214–228Cite as

Evolving Allocation Rules for Beam Search Heuristics in Assembly Line Balancing

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12691))

Abstract

We study the evolution of rules that define how to assign tasks to workstations in heuristic procedures for assembly line balancing. In assembly line balancing, a set of partially ordered tasks has to be assigned to workstations. The variant we consider, known as the assembly line worker assignment and balancing problem (ALWABP), has a fixed number of machines and workers, and different workers need different times to execute the tasks. A solution is an assignment of tasks and workers to workstations satisfying the partial order of the tasks, and the problem is to find a solution that maximizes the production rate of the assembly line. These problems are often solved by station-based assignment procedures, which use heuristic rules to select the tasks to be assigned to stations. There are many selection rules available in the literature. We show how efficient rules can be evolved, and demonstrate that rules evolved for simple assignment procedures are also effective in stochastic heuristic procedures using beam search, leading to improved heuristics.

Our research has been supported by CNPq (grant 420348/2016-6), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, and by Google Research Latin America (grant 25111).

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Notes

  1. 1.

    We write \([n]=\{1,2,\ldots ,n\}\).

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Authors and Affiliations

  1. Instituto de Informática, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, Porto Alegre, Rio Grande do Sul, Brazil

    João Pedro Gonçalves Moreira & Marcus Ritt

Authors
  1. João Pedro Gonçalves Moreira
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  2. Marcus Ritt
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Correspondence to Marcus Ritt .

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Editors and Affiliations

  1. Queen’s University, Kingston, ON, Canada

    Ting Hu

  2. University of Coimbra, Coimbra, Portugal

    Nuno Lourenço

  3. University of Trieste, Trieste, Italy

    Eric Medvet

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Gonçalves Moreira, J.P., Ritt, M. (2021). Evolving Allocation Rules for Beam Search Heuristics in Assembly Line Balancing. In: Hu, T., Lourenço, N., Medvet, E. (eds) Genetic Programming. EuroGP 2021. Lecture Notes in Computer Science(), vol 12691. Springer, Cham. https://doi.org/10.1007/978-3-030-72812-0_14

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  • DOI: https://doi.org/10.1007/978-3-030-72812-0_14

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  • Online ISBN: 978-3-030-72812-0

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