Fuzzy Decision-Making Algorithms: Mathematical Optimization, Metaheuristic Optimization, Supply Chain Management

This book explores the blend of metaheuristic optimization algorithms and fuzzy decision-making paradigms to reinforce supply chain sustainability and viability. The combination of mathematical and metaheuristic optimization methods based on natural processes and fuzzy decision-making allows models to be built that can effectively deal with the multifaceted issues of contemporary supply chains. This book provides various techniques of decision-making, such as entropy measures, distance measures, coefficient correlation, aggregating operators, TOPSIS, EDAS, etc. This books overcomes the drawbacks of existing fuzzy decision-making methods This book also provides case studies in which metaheuristic decision-making algorithms have been applied to enhance the sustainability and viability of supply chains. One such notable example is green supplier selection in supply chain management. The changing supply chain management landscape offers many areas for future research, like investigating the intersection of mathematical and metaheuristic fuzzy decision-making algorithms with new technologies such as the Internet of Things (IoT) and artificial intelligence, which can create more responsive and adaptive supply chains.