A bi-level optimisation approach for assembly line design using a nested genetic algorithm. Issue 24 (17th December 2021)

• Record Type: Journal Article
• Authors: Leiber, Daria; Reinhart, Gunther
• Is Part Of: International journal of production research. Volume 59:Issue 24(2021)
• Page Start: 7560
• Page End: 7575
• Publication Date: 2021-12-17
• Subjects: assembly line balancing -- assembly line design -- assembly line planning -- layout planning -- nested genetic algorithm -- bi-level optimisation; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2020.1845411
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : This article presents a novel approach for the automated design of assembly lines that combines the assembly line balancing problem with resource selection and the positioning of the chosen resources into one single optimisation problem. Existing approaches for the automated planning of assembly plants either focus on one planning step or work through different planning steps sequentially. So far, no method exists that sufficiently takes into account the interdependency between the selection and positioning of resources. This article addresses this problem by presenting a bi-level optimisation approach for the automated design of assembly lines. A nested genetic algorithm is used to solve an assembly line balancing problem that includes the selection of production resources while simultaneously considering the layouting options for the chosen resources. Three examples for the evaluation and validation of the algorithm are presented. The presented approach is economically promising as the design of assembly lines requires a lot of expert knowledge and is still mostly done manually.