Mixed-Integer Linear Programming (MILP) for Garment Line Balancing

This applied research article explores the application of Mixed-Integer Linear Programming (MILP) to address line-balancing challenges in the garment industry, focusing on optimizing production processes under multiple constraints. By integrating MILP with Lean Methodology principles, the study demonstrates significant improvements in operational efficiency and cost-effectiveness. The case study, conducted in collaboration with Prof Dr Ray WM Kong, highlights the successful implementation of MILP using IBM CPLEX Studio to optimize production order quantities across online and offline operations. The results reveal a remarkable reduction in labour costs, exceeding 50%, while effectively managing resource capacity and demand constraints. This study not only validates the theoretical underpinnings of MILP in resolving line-balancing issues but also underscores its practical applicability in modernizing garment production. The findings contribute valuable insights into the potential of advanced optimization techniques to enhance competitiveness and sustainability in the garment industry. This abstract succinctly captures the essence of the research, emphasizing the methodology, results, and significance of the study.

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Publication Details

Journal
ArXiv.org
Published
2025-03-07
DOI
https://doi.org/10.5281/zenodo.14942910
Primary Topic
Assembly Line Balancing Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Mixed-Integer Linear Programming (MILP) for Garment Line Balancing

Ning Ding, Ray Wai Man Kong, Theodore Ho Tin Kong
ArXiv.org
Assembly Line Balancing Optimization
article

Mixed-Integer Linear Programming (MILP) for Garment Line Balancing

Ning Ding, Ray Wai Man Kong, Theodore Ho Tin Kong
article en

Abstract

This applied research article explores the application of Mixed-Integer Linear Programming (MILP) to address line-balancing challenges in the garment industry, focusing on optimizing production processes under multiple constraints. By integrating MILP with Lean Methodology principles, the study demonstrates significant improvements in operational efficiency and cost-effectiveness. The case study, conducted in collaboration with Prof Dr Ray WM Kong, highlights the successful implementation of MILP using IBM CPLEX Studio to optimize production order quantities across online and offline operations. The results reveal a remarkable reduction in labour costs, exceeding 50%, while effectively managing resource capacity and demand constraints. This study not only validates the theoretical underpinnings of MILP in resolving line-balancing issues but also underscores its practical applicability in modernizing garment production. The findings contribute valuable insights into the potential of advanced optimization techniques to enhance competitiveness and sustainability in the garment industry. This abstract succinctly captures the essence of the research, emphasizing the methodology, results, and significance of the study.

ArXiv.org
Openalex Percentile: Top 59%
Assembly Line Balancing Optimization
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