Springer Intelligent Decision-making Models for Production and Retail Operations

Product Description This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting. Review “The book aims at providing an overview of various models and approaches to support decision-making in production and retail operations. … this book results interesting for researchers and students who want to approach the topic of intelligent decision-making models for the first time … . is also a precious instrument for those researchers who are familiar with some of the proposed intelligent techniques and models and want to increase their knowledge about them and the other intelligent techniques … .” (Elisa Negri, Production Planning & Control, Vol. 28 (15), August, 2017) From the Back Cover This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting. About the Author Zhaoxia Guo Research Areas Production scheduling and optimization, Sales forecasting, Decision support systems, Computational intelligence Education 09/2004-08/2007, Ph.D , The Hong Kong Polytechnic University, Hong Kong 09/2000-03/2003, M.Sc. in Control Theory and Control Engineering, Donghua University, Shanghai, China 09/1996-06/2000, Bachelor in Automatic Control, Donghua University, Shanghai, China Working Experience 2012.09- Present, Associate Professor, Business School, Sichuan University, China 2013.12- 2014.12, Honorary associate, University of Wisconsin-Madison, US 2008.12-2012.08, Postdoctoral fellow, The Hong Kong Polytechnic University, Hong Kong 2007.09-2008.11, IT/System In Charge, Genexy Company Limited, Hong Kong 2003.3-2004.8, Assistant lecturer, Donghua University, China Awards 2nd Prize in IMB Innovation Award 2009 (Category: Research and Development), Awarded by The European Commission of the Industry Research, IMB 2009 World of Textile Processing, German, 3rd Awardee Gold Award in Most Innovative Use of EPC/RFID, Hong Kong RFID Awards 2012, Hong Kong, 2nd Awardee Professional Activities Editorial member, International Journal of Engineering Mathematics, Advanced Engineering Technology and Application; Member, International Institute of Forecasters, Association for Information Systems; The 10th IEEE International Conference on Industrial Informatics (INDIN 2012), Session Cha