Optimizing Decision Making in the Apparel Supply Chain Using Artificial Intelligence (AI)

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 AI 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. Key decision points in the apparel supply chain and the fundamentals of artificial intelligence techniques are the focus of the opening chapters, before the book proceeds to discuss the use of neural networks, genetic algorithms, fuzzy set theory and extreme learning machines for intelligent sales forecasting and intelligent product cross-selling systems. - 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

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.