A hybrid genetic algorithm for the simple assembly line balancing problem with a fixed number of workstations

Eduardo Álvarez-Miranda, Jordi Pereira, Harold Torrez-Meruvia, Mariona Vilà

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The assembly line balancing problem is a classical optimisation problem whose objective is to assign each production task to one of the stations on the assembly line so that the total efficiency of the line is maximized. This study proposes a novel hybrid method to solve the simple version of the problem in which the number of stations is fixed, a problem known as SALBP-2. The hybrid differs from previous approaches by encoding individuals of a genetic algorithm as instances of a modified problem that contains only a subset of the solutions to the original formulation. These individuals are decoded to feasible solutions of the original problem during fitness evaluation in which the resolution of the modified problem is conducted using a dynamic programming based approach that uses new bounds to reduce its state space. Computational experiments show the efficiency of the method as it is able to obtain several new best-known solutions for some of the benchmark instances used in the literature for comparison purposes.

Original languageEnglish
Article number2157
JournalMathematics
Volume9
Issue number17
DOIs
StatePublished - Sep 2021
Externally publishedYes

Keywords

  • Assembly lines
  • Hybrid genetic algorithm
  • Line balancing
  • Manufacturing

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