Title: Integrated mathematical model to optimise workstations in garment assembly line balancing

Authors: Nhat Quyen Phan; Thi Diem Chau Le

Addresses: Department of Industrial Systems Engineering, Faculty of Mechanical, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam ' Department of Industrial Systems Engineering, Faculty of Mechanical, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Abstract: The study presents an integrated approach that combines ant colony optimisation (AntCO) and dynamic Min-Max normalisation (DMMN), namely the DMMN-AntCO, to address the assembly line balancing problem (ALBP) in the textile industry. The primary objective is to develop a practical approach for decision-making support by minimising workstation processing time deviation from takt time (TT) and reducing operational and setup costs. AntCO generates solutions iteratively using pheromone trails, while DMMN dynamically updates objective function values, allowing unbiased solution comparisons. Experimental outcomes show that the DMMN-AntCO significantly improves workload balance through the smooth index, decreasing from 8.72 to 6.01, and lowers production costs by over 360 USD compared to traditional methods. This study has provided a robust algorithm to optimise production line balancing, reduce costs, and enhance resource utilisation. The results confirm the effectiveness of the DMMN-AntCO method, thereby strengthening the fast response and competitive advantage of companies in the textile industry.

Keywords: ant colony optimisation; dynamic Min-Max normalisation; DMMN; multi-objective optimisation; assembly line balancing; task allocation; meta-heuristic algorithm; textile industry; workload balance.

DOI: 10.1504/IJMDM.2025.149602

International Journal of Management and Decision Making, 2025 Vol.24 No.6, pp.614 - 632

Received: 12 Apr 2025
Accepted: 22 Jun 2025
Published online: 07 Nov 2025 *

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