This item is in: Textile > Clothing

Optimizing decision making in the apparel supply chain using artificial intelligence (AI): From production to retail

W K Wong, Z X Guo and S Y S Leung, Hong Kong Polytechnic University, China

Woodhead Publishing Series in Textiles No. 143

 - helps the reader gain an understanding of the key decision points in the apparel supply chain
 - discusses the fundamentals of artificial intelligence techniques for apparel management techniques
 - considers the use of neural networks in selecting the location of apparel manufacturing plants
 - reviews intelligent product cross-selling systems in fashion retailing using RFID technology

Practitioners in apparel manufacturing and retailing enterprises in the fashion industry, ranging from senior to front line management, constantly face complex and critical decisions. There has been growing interest in the use of artificial intelligence (AI) techniques to enhance this process, and a number of techniques have already been successfully applied to apparel production and retailing. Optimizing decision making in the apparel supply chain using artificial intelligence (AI): From production to retail provides detailed coverage of these techniques, outlining how they are used to assist decision makers in tackling key supply chain problems.

Understanding key decision points in the apparel supply chain and the fundamentals of artificial intelligence techniques for apparel management applications are the focus of the opening chapters. Optimizing decision making in clothing management using artificial intelligence (AI) then proceeds to discuss the use of neural networks in selecting the location of apparel manufacturing plants, optimization of apparel production order planning scheduling using genetic algorithms, and the employment of evolutionary strategies and neural networks to optimize cut order and marker planning. The use of genetic algorithms and fuzzy set theory in the optimization of fabric spreading and cutting schedules is discussed, followed by the overall optimization of apparel production systems using genetic algorithms. Intelligent sales forecasting for fashion retailing using harmony search algorithms and extreme learning machines is then considered, before the book concludes with a review of intelligent product cross-selling systems in fashion retailing using radio frequency identification (RFID) technology, fuzzy logic and rule-based expert systems.

Drawing on the in-depth knowledge of its expert authors, Optimizing decision making in the apparel supply chain using artificial intelligence (AI): From production to retail is a practical guide for all those involved in the research, design and management of apparel production and retail chains. It also provides a clear overview of the topic for academics interested in the development of this technology.

Published in association with The Textile Institute

£125.00 / US$210.00 / €150.00

An e-book version of this title is available to purchase as part of a Collection or Pick n Mix or by Chapter. Visit Woodhead Publishing Online

About the authors

W. K. Wong and S. Y. S. Leung are based at the Institute of Textiles and Clothing, The Hong Kong Polytechnic University, China.

Z. X. Guo is based at the Business School, at Sichuan University, China.

Titles which may also be of interest:
Ergonomics in the garment industry
Textile-led design for the active ageing population

Contents

Understanding key decision points in the apparel supply chain
W K Wong, The Hong Kong Polytechnic University, China
 - Introduction
 - Selection of plant locations
 - Production scheduling and assembly line balancing control
 - Cutting room
 - Retailing

Fundamentals of artificial intelligence techniques for apparel management applications
Z X Guo, Sichuan University, China and W K Wong, The Hong Kong Polytechnic University, China
 - Artificial intelligence (AI) techniques: a brief overview
 - Rule-based expert system
 - Evolutionary optimization techniques
 - Feed-forward neural networks (FNNs)
 - Fuzzy logic
 - Conclusions
 - References

Selecting the location of apparel manufacturing plants using neural networks
W K Wong, X H Zeng and K F Au, The Hong Kong Polytechnic University, China
 - Introduction
 - Classification methods using artificial neural networks
 - Classifying decision models for the location of clothing plants
 - Classification using unsupervised artificial neural networks (ANN)
 - Classification using supervised artificial neural networks (ANN)
 - Conclusion
 - Acknowledgements
 - References

Optimizing apparel production order planning scheduling using genetic algorithms
Z X Guo, Sichuan University, China, and W K Wong, S Y S Leung, J T Fan, and S F Chan, The Hong Kong Polytechnic University, China
 - Introduction
 - Problem formulation
 - Dealing with uncertain completion and start times
 - Genetic algorithms for order scheduling
 - Experimental results and discussion
 - Conclusions
 - Acknowledgement
 - References

Optimizing cut order planning in apparel production using evolutionary strategies
W K Wong and S Y S Leung The Hong Kong Polytechnic University, China
 - Introduction
 - Formulation of the cut order planning (COP) decision-making model
 - Genetic COP optimization
 - An example of a genetic optimization model for COP
 - Conclusions
 - Acknowledgement
 - References

Optimizing marker planning in apparel production using evolutionary strategies and neural networks
W K Wong, X X Wang The Hong Kong Polytechnic University, China, and Z X Guo, Sichuan University, China
 - Introduction
 - Packing method for optimised marker packing
 - Evolutionary strategy (ES) for optimising marker planning
 - Experiments to evaluate performance
 - Conclusion
 - Acknowledgement
 - References

Optimizing fabric spreading and cutting schedules in apparel production using genetic algorithms and fuzzy set theory
W K Wong, CK Kwong, P Y Mok and W H Ip, The Hong Kong Polytechnic University, China
 - Introduction
 - Problem formulation in fabric cutting operations
 - Genetic optimization of fabric scheduling
 - Case studies using real production data
 - Conclusions
 - Acknowledgement
 - References

Optimizing apparel production systems using genetic algorithms
W K Wong, P Y Mok and S Y S Leung, The Hong Kong Polytechnic University, China
 - Introduction
 - Problem formulation in sewing operations
 - Genetic optimisation of production line balancing
 - Experimental results
 - Conclusions
 - Acknowledgement
 - References

Intelligent sales forecasting for fashion retailing using harmony search algorithms and extreme learning machines
W K Wong, The Hong Kong Polytechnic University, China and Z X Guo, Sichuan University, China
 - Introduction
 - Hybrid intelligent model for medium-term fashion sales forecasting
 - Evaluating model performance with real sales data
 - Experimental results and analysis
 - Assessing forecasting performance
 - Conclusions
 - Acknowledgement
 - References

Intelligent product cross-selling system in fashion retailing using radio frequency identification (RFID) technology, fuzzy logic and rule-based expert system
W K Wong and S Y S Leung, The Hong Kong Polytechnic University, China, Z X Guo, Sichuan University, China, Z H Zeng and P Y Mok, The Hong Kong Polytechnic University, China
 - Introduction
 - Radio frequency identification (RFID)-enabled smart dressing system (SDS)
 - Intelligent product cross-selling system (IPCS)
 - Implementation of the RFID-enabled SDS and IPCS
 - Evaluation of the RFID-enabled SDS
 - Assessing the use of RFID technology in fashion retailing
 - Conclusions
 - Acknowledgment
 - References