Investigating two variants of the sequence-dependent robotic assembly line balancing problem by means of a split-based approach. Issue 7 (3rd April 2023)

• Record Type: Journal Article
• Authors: Lahrichi, Youssef; Damand, David; Deroussi, Laurent; Grangeon, Nathalie; Norre, Sylvie
• Is Part Of: International journal of production research. Volume 61:Issue 7(2023)
• Page Start: 2322
• Page End: 2338
• Publication Date: 2023-04-03
• Subjects: Assembly line balancing -- robotic assembly line -- sequence-dependent setup times -- polynomial case -- metaheuristic; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2022.2062266
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : The Robotic Assembly Line Balancing Problem (RALBP) is a joint optimisation problem that is concerned with assigning both assembly operations and robots to workstations that are placed within a straight line. RALBP-2 is the particular problem where the cycle time, which is the maximum time spent on a workstation by the product being assembled, is minimised while the number of workstations is fixed. Sequence-dependent setup times are considered which raises the problem of sequencing the operations assigned to each workstation. Both the durations of the operations and the setup times depend on the robot. Two different variants are identified from literature. The first variant assumes that, given a set of types of robots, each type of robot can be assigned to multiple workstations without any limitation. Given a set of robots, the second variant forces each robot to be assigned to at most one workstation. Both assumptions are studied in this paper. The particular case of a given giant sequence of operations is solved thanks to a polynomial optimal algorithm. The latter algorithm, called split, is then embedded in a metaheuristic framework that explores the space of giant sequences. Benchmark data sets from literature are considered in the experimental section. A comparative study with other methods from literature shows the competitiveness of the suggested approach.