Advanced Optimization and Decision-Making Techniques in Textile Manufacturing

Optimization and decision making are integral parts of any manufacturing process and management system. The objective of this book is to demonstrate the confluence of theory and applications of various types of multi-criteria decision making and optimization techniques with reference to textile manufacturing and management. Divided into twelve chapters, it discusses various multi-criteria decision-making methods such as AHP, TOPSIS, ELECTRE, and optimization techniques like linear programming, fuzzy linear programming, quadratic programming, in textile domain. Multi-objective optimization problems have been dealt with two approaches, namely desirability function and evolutionary algorithm.

Key Features

• Exclusive title covering textiles and soft computing fields including optimization and decision making





• Discusses concepts of traditional and non-traditional optimization methods with textile examples





• Explores pertinent single-objective and multi-objective optimizations





• Provides MATLAB coding in the Appendix to solve various types of multi-criteria decision making and optimization problems





• Includes examples and case studies related to textile engineering and management

Dr. Anindya Ghosh completed his B.Tech. in Textile Technology in 1997 from College of Textile Technology, Berhampore (Calcutta University), India. After that he worked in a textile spinning industry for one year as a shift engineer. He completed his M. Tech. and PhD in Textile Engineering from Indian Institute of Technology, Delhi, India in 2000 and 2004 respectively. He is a recipient of Career Award for Young Teacher-2009 from AICTE, India. He has more than 14 years experience in Teaching. Currently he is working as an Associate Professor in Government College of Engineering & Textile Technology, Berhampore. His research work involves yarn manufacturing, Yarn and fabric structures, modeling and simulation, optimization and decision making techniques. He has published more than 70 papers in various referred journals.

Dr. Prithwiraj Mal is post graduate in Textile Engineering from Indian Institute of Technology Delhi. He has almost 16 years of cumulative experience in both industry and academics. He completed PhD from Jadavpur University, Kolkata in 2017. Prithwiraj Mal has joined NIFT in 2008 and currently posted in NIFT Hyderabad as Assistant Professor in Department of Textile Design. His research work involves comfort, optimization, decision making techniques & product development. He has published more than 20 papers in various referred journals and presented / published papers in conferences in national and international levels.

Dr. Abhijit Majumdar is working as Professor in Department of Textile Technology of Indian Institute of Technology Delhi, India. A graduate from Calcutta University, with gold medal in Textile Technology, he completed his post graduate and Ph.D degrees from IIT Delhi and Jadavpore University, Kolkata, respectively. His research areas include protective textiles (soft armour, antibacterial, UV etc.), soft computing applications and sustainable supply chain management. He has completed research projects funded by Department of Science and Technology (DST), Defense Research and Development Organization (DRDO) and Council for Scientific and Industrial Research (CSIR), He has published 85 research papers in international refereed journals and guided seven Ph.D students. He has authored one book entitled 'Principles of Woven Fabric Manufacturing' published by CRC press. He has also edited two books published by Woodhead Publisher, U. K. and authored one monograph (Textile Progress) published by Taylor and Francis. He is the associate editor of Journal of the Institution of Engineers (India) Series E (Chemical and Textile Engineering) published by Springer. He is a recipient of Outstanding Young Faculty Fellowship (2009-2014) of IIT Delhi, Teaching Excellence Award (2015) of IIT Delhi and Gandhian Young Technological Innovation Award (2017).