Titlebook: Intelligent Decision-making Models for Production and Retail Operations; Zhaoxia Guo Book 2016 Springer-Verlag Berlin Heidelberg 2016 Comp

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New Developments and Decision-makings in Production and Retailing,and decision-makings because some new decision-making problems and problem features emerge and have to be handled. This chapter then reviews previous studies on decision-making problems in production and retailing, including production planning, production scheduling, assembly line balancing, and sa

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Fundamentals of Intelligent Decision-Making Techniques,ues are introduced firstly. Some representative CI techniques, especially those that have been usually used in solving decision-making problems in production and retail operations, are then presented to help readers understand CI techniques used in subsequent chapters. These techniques include evolu

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A Bilevel Intelligent Optimization Model for Assembly Line Scheduling with Flexible Operation Assigctives of minimizing the weighted sum of tardiness and earliness penalties and balancing the production flow of the flexible assembly line. A bilevel genetic algorithm-based optimization approach is developed to handle this scheduling problem, in which a novel chromosome representation is presented

ONYM

A Bilevel Multi-parent Genetic Optimization Model for Flexible Assembly Line Balancing with Work-Shroblem is presented with the objectives of meeting the desired cycle time of each order and minimizing the total idle time of the assembly line. An optimization model is developed to handle the addressed problem, which comprises two parts. A bilevel multi-parent genetic optimization approach, bileve

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An Evolution Strategy-Based Multi-objective Optimization Model for Order Planning with Multiple Prole plants, multiple production departments, and multiple production processes. The mathematical model of this problem is established first. An evolution strategy-based multi-objective optimization approach is then developed to handle this problem, in which a novel .-evolution strategy process with s

低能儿

A Multi-objective Hybrid Intelligent Optimization Model for Order Planning with Uncertainties,rder manufacturing. The mathematical model of this problem is presented. A novel multi-objective hybrid intelligent optimization approach, combining a multi-objective memetic optimization process, a Monte Carlo simulation technique, and a heuristic pruning technique, is developed to handle this prob

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An RFID- and Cloud-Based Intelligent Decision Support System Architecture for Production Tracking ation tracking and scheduling. This chapter presents a radio frequency identification (RFID)- and cloud-based intelligent decision support system architecture to handle production tracking and scheduling in a distributed manufacturing environment. A pilot implementation of the architecture is perform

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A Neural Network-Based Forecasting Model for Univariate Sales Forecasting, on the Apollonian networks. In terms of three types of publicly available benchmark data, a series of experiments are conducted to compare the forecasting performance of the proposed SCNNs, randomly connected SCNNs and traditional feed-forward neural networks. The comparison results show that the p