A memetic algorithm for the cost-oriented robotic assembly line balancing problem

Jordi Pereira, Marcus Ritt, Óscar C. Vásquez

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

In order to minimize costs, manufacturing companies have been relying on assembly lines for the mass production of commodity goods. Among other issues, the successful operation of an assembly line requires balancing work among the stations of the line in order to maximize its efficiency, a problem known in the literature as the assembly line balancing problem, ALBP. In this work, we consider an ALBP in which task assignment and equipment decisions are jointly considered, a problem that has been denoted as the robotic ALBP. Moreover, we focus on the case in which equipment has different costs, leading to a cost-oriented formulation. In order to solve the problem, which we denote as the cost-oriented robotic assembly line balancing problem, cRALBP, a hybrid metaheuristic is proposed. The metaheuristic embeds results obtained for two special cases of the problem within a genetic algorithm in order to obtain a memetic algorithm, applicable to the general problem. An extensive computational experiment shows the advantages of the hybrid approach and how each of the components of the algorithm contributes to the overall ability of the method to obtain good solutions.

Original languageEnglish
Pages (from-to)249-261
Number of pages13
JournalComputers and Operations Research
Volume99
DOIs
StatePublished - Nov 2018
Externally publishedYes

Keywords

  • Cost-oriented line balancing
  • Hybrid algorithms
  • Line balancing
  • Robotic assembly line

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