Fr. 229.00

Optimizing Decision Making in Apparel Supply Chain Using Artificial - From Production to Retail

English · Hardback

Shipping usually within 1 to 3 weeks (not available at short notice)

Description

Read more

Informationen zum Autor W. K. Wong is full professor at The Hong Kong Polytechnic University, Hong Kong and is currently with the endowed professorship title as Cheng Yik Hung Professor in Fashion. His areas of research range from computer vision to artificial intelligence with applications in the textile and fashion industries. He has published over hundred research articles in high-impact artificial intelligence related journals and serves as editorial board member of several journals. He also provides consultancy services to fashion and textile companies in the industry. S. Y. S. Leung is based at the Institute of Textiles and Clothing, The Hong Kong Polytechnic University, China.

List of contents

Woodhead Publishing Series in Textiles
Preface
Acknowledgements
Chapter 1: Understanding key decision points in the apparel supply chain
Abstract:
1.1 Introduction
1.2 Selection of plant locations
1.3 Production scheduling and assembly line balancing control
1.4 Cutting room
1.5 Retailing
Chapter 2: Fundamentals of artificial intelligence techniques for apparel management applications
Abstract:
2.1 Artificial intelligence (AI) techniques: a brief overview
2.2 Rule-based expert systems
2.3 Evolutionary optimization techniques
2.4 Feedforward neural networks (FNNs)
2.5 Fuzzy logic
2.6 Conclusions
Chapter 3: Selecting the location of apparel manufacturing plants using neural networks
Abstract:
3.1 Introduction
3.2 Classification methods using artificial neural networks
3.3 Classifying decision models for the location of clothing plants
3.4 Classification using unsupervised artificial neural networks (ANN)
3.5 Classification using supervised ANN
3.6 Conclusion
3.7 Acknowledgements
3.9 Appendix: performance of back propagation (BP) and learning vector quantization (LVQ) with a different number of hidden neurons
Chapter 4: Optimizing apparel production order planning scheduling using genetic algorithms
Abstract:
4.1 Introduction
4.2 Problem formulation
4.3 Dealing with uncertain completion and start times
4.4 Genetic algorithms for order scheduling
4.5 Experimental results and discussion
4.6 Conclusions
4.7 Acknowledgement
Chapter 5: Optimizing cut order planning in apparel production using evolutionary strategies
Abstract:
5.1 Introduction
5.2 Formulation of the cut order planning (COP) decision-making model
5.3 Genetic COP optimization
5.4 An example of a genetic optimization model for COP
5.5 Conclusions
5.6 Acknowledgement
5.8 Appendix: comparison between industrial practice and proposed COP decision-making model
Chapter 6: Optimizing marker planning in apparel production using evolutionary strategies and neural networks
Abstract:
6.1 Introduction
6.2 Packing method for optimized marker packing
6.3 Evolutionary strategy (ES) for optimizing marker planning
6.4 Experiments to evaluate performance
6.5 Conclusion
Chapter 7: Optimizing fabric spreading and cutting schedules in apparel production using genetic algorithms and fuzzy set theory
Abstract:
7.1 Introduction
7.2 Problem formulation in fabric-cutting operations
7.3 Genetic optimization of fabric scheduling
7.4 Case studies using real production data
7.5 Conclusions
7.6 Acknowledgement
7.8 Appendix: nomenclature
Chapter 8: Optimizing apparel production systems using genetic algorithms
Abstract:
8.1 Introduction
8.2 Problem formulation in sewing operations
8.3 Genetic optimization of production line balancing
8.4 Experimental results
8.5 Conclusions
8.6 Acknowledgement
8.8 Appendix: nomenclature
Chapter 9: Intelligent sales forecasting for fashion retailing using harmony search algorithms and extreme learning machines
Abstract:
9.1 Introduction
9.2 Hybrid intelligent model for medium-term fashion sales forecasting
9.3 Evaluating model performance with real sales data
9.4 Experimental results and analysis
9.5 Assessing forecasting performance
9.6 Conclusions
6.7 Acknowledgement
Chapter 10: Intelligent product cross-selling system in fashion retailing using radio frequency identification (RFID) technology, fuzzy logic and rule-based expert system
Abstract:
10.1 Introduction
10.2 Radio frequency identificati

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.