INTEGRATED ARTIFICIAL IMMUNE SYSTEM AND TAGUCHI APPROACH FOR PRODUCTION SCHEDULING IN THE GARMENT INDUSTRY

Authors

  • Chia-Nan Wang Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
  • Tram Thi Mai Nguyen Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan | Department of Business Administration, Faculty of Economics, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam

DOI:

https://doi.org/10.23055/ijietap.2024.31.2.9747

Abstract

Presently, Vietnam is the third-largest garment exporter in the world, with a 6.1% market share. Nevertheless, Vietnam's apparel industry faces fierce competition from other countries making low-cost garments. Enterprises must enhance many aspects to survive in a competitive market, including ensuring product availability at optimal prices. To achieve this, all production managers shall schedule production while factoring in early and late production costs. This study presents a novel integer nonlinear programming model to minimize the cost of earliness and tardiness, considering weight for storage. The metaheuristic utilized to solve the problem in this work is the integrated artificial immune system (AIS) algorithm and the Taguchi technique. Subsequently, implementing a sensitivity analysis to ascertain the weight for storage is a crucial decision faced by production managers. Finally, this study compares the proposed method to the Vietnamese garment industry's current technique and shows its suitability for production scheduling in this sector.

Downloads

Published

2024-04-18

How to Cite

Wang, C.-N., & Nguyen, T. T. M. (2024). INTEGRATED ARTIFICIAL IMMUNE SYSTEM AND TAGUCHI APPROACH FOR PRODUCTION SCHEDULING IN THE GARMENT INDUSTRY. International Journal of Industrial Engineering: Theory, Applications and Practice, 31(2). https://doi.org/10.23055/ijietap.2024.31.2.9747

Issue

Section

Production Planning and Control