Applying Genetic Algorithm for Line Balancing Problem in Garment Manufacture

Hoa Nguyen Thi Xuan (), Anh Vu Hai and Anh Nguyen Quang
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Hoa Nguyen Thi Xuan: Hanoi University of Science and Technology, School of Economics and Management
Anh Vu Hai: Hanoi University of Science and Technology, School of Economics and Management
Anh Nguyen Quang: Hanoi University of Science and Technology, School of Information and Communication Technology

A chapter in Proceedings of the International Conference on Emerging Challenges: Strategic Adaptation in the World of Uncertainties (ICECH 2022), 2023, pp 203-220 from Springer

Abstract: Abstract The garment industry is one of the most intensely competitive in the world, and productivity is essential to sustaining that competitiveness. As one of the sectors that utilizes a large number of people and various activities at workstations, the garment industry is one that places a high priority on increasing productivity and reducing production costs. One of the biggest problems the garment sector has is line balance, which arises from the way the work is organized on the line and the coordination between workers, machines, and stages. Therefore, in an effort to increase productivity and reduce production costs, the line balancing problem is posed. In order to handle the nonlinear programming challenge, the GA heuristics technique was employed in this study. This study was tested with data from a clothing company to determine the efficacy of line balancing. Based on the results of line balancing, line managers can quickly balance lines to to minimize production cycle time and utilize workforce on the assembly line.

Keywords: Line balancing; genetic algorithms; efficiency (search for similar items in EconPapers)
Date: 2023
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DOI: 10.2991/978-94-6463-150-0_15

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