Introduction.- Fundamentals of intelligent decision-making techniques.- An intelligent decision-making framework for production planning and control.- An intelligent optimization model for order scheduling at factory level.- A bi-level intelligent optimization model for assembly line scheduling with flexible operation assignment.- A bi-level multi-parent genetic optimization model for flexible assembly line balancing with work-sharing and workstation revisiting.- An evolution strategy-based multi-objective optimization model for order planning with multiple production departments.- A multi-objective memetic optimization model for order planning with uncertainties.- A harmony search-based hybrid intelligent model for order planning with learning effects.- An RFID-and-cloud-based intelligent decision support system architecture for production monitoring and scheduling.- A neural network-based forecasting model for univariate sales forecasting.- An extreme learning machine-based intelligent decision-making model for multivariate sales forecasting.- Conclusion.

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.