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An easy-to-read introduction to the concepts associated with the creation of optimization models for production planning starts off this book. These concepts are then applied to well-known planning models, namely mrp and MRP II. From this foundation, fairly sophisticated models for supply chain management are developed. Another unique feature is that models are developed with an eye toward implementation. In fact, there is a chapter that provides explicit examples of implementation of the basic models using a variety of popular, commercially available modeling languages.
This book offers a collection of original peer-reviewed contributions presented at the 6th International Congress on Design and Modeling of Mechanical Systems (CMSM’2015), held in Hammamet, Tunisia, from the 23rd to the 25th of March 2015. It reports on both recent research findings and innovative industrial applications in the fields of mechatronics and robotics, dynamics of mechanical systems, fluid structure interaction and vibroacoustics, modeling and analysis of materials and structures, and design and manufacturing of mechanical systems. Since its first edition in 2005, the CMSM Congress has been held every two years with the aim of bringing together specialists from universities and industry to present the state-of-the-art in research and applications, discuss the most recent findings and exchange and develop expertise in the field of design and modeling of mechanical systems. The CMSM Congress is jointly organized by three Tunisian research laboratories: the Mechanical Engineering Laboratory of the National Engineering School of Monastir; the Mechanical Laboratory of Sousse, part of the National Engineering School of Sousse; and the Mechanical, Modeling and Manufacturing Laboratory at the National Engineering School of Sfax.
This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions. These proceedings contain papers in the fields of Machine Learning, Computational Optimization and DataScience presenting a substantial array of ideas, technologies, algorithms, methods and applications.
This book examines the Capacitated Lot Sizing Problem (CLSP) in process industries. In almost all process industries, there are situations where products have short/long setup times, and the setup of the product and its subsequent production are carried over, across consecutive periods. The setup of a product is carried over across more than one successive period in the case of products having long setup times. A product having short setup has its setup time less than the capacity of the period in which it is setup. The setup is immediately followed by its production of the product and it may also be carried over, across successive time period(s). Many process industries require production of a product to occur immediately after its setup (without the presence of idle time between the setup and production of the product), and they also require the product to be continuously produced without any interruption. This book considers a single-machine, single-level and multiple-item CLSP problem. This book introduces the Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover across periods (CLSP-PCSC). Mathematical models are proposed which are all encompassing that they can handle continuous manufacturing (as in process industries), and also situations where the setup costs and holding costs are product dependent and time independent/time dependent, with possible backorders, and with other appropriate adaptations. Comprehensive heuristics are proposed based on these mathematical models to solve the CLSP-PCSC. The performance of the proposed models and heuristics are evaluated using problem instances of various sizes. This book also covers mathematical models developed for the Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover across periods, and with Sequence-Dependent Setup Times and Setup Costs (CLSP-SD-PCSC). These models allow the presence of backorders and also address real-life situations present in process industries such as production of a product starting immediately after its setup and its uninterrupted production carryover across periods, along with the presence of short/long setup times. Heuristics proposed for the CLSP-PCSC can be extended to address the CLSP problem with sequence dependent setup costs and setup times. All the models and heuristics proposed in this book address some real-life considerations present in process industries.
This tutorial contains written versions of seven lectures on Computational Combinatorial Optimization given by leading members of the optimization community. The lectures introduce modern combinatorial optimization techniques, with an emphasis on branch and cut algorithms and Lagrangian relaxation approaches. Polyhedral combinatorics as the mathematical backbone of successful algorithms are covered from many perspectives, in particular, polyhedral projection and lifting techniques and the importance of modeling are extensively discussed. Applications to prominent combinatorial optimization problems, e.g., in production and transport planning, are treated in many places; in particular, the book contains a state-of-the-art account of the most successful techniques for solving the traveling salesman problem to optimality.
Advanced modeling techniques are a necessary tool in order to design and manage manufacturing systems effectively. This book contains a set of tutorial chapters on topics ranging from aggregate production planning to real time control, including predictive and reactive scheduling, flow management in assembly systems, simulation of robotic cells, design of manufacturing systems under uncertainty and a historical perspective on production management philosophies. The book will be of interest both to researchers and practitioners, including graduate students in Manufacturing Engineering and Operations Research.
Designed by practitioners for practitioners, Supply Chain Management and Logistics: Innovative Strategies and Practical Solutions provides a wide-spectrum resource on many different aspects involved in supply chain management, including contemporary applications. With contributions from leading experts from all over the world, the book includes innovative strategies and practical solutions that address problems encountered by enterprise in management of supply chain and logistics. It details general techniques and specific approaches to a broad range of important, inspiring, and unanswered questions in the field. The book is organized around four major research themes in supply chain management: 1) supply chain strategy and coordination, 2) supply chain network optimization, 3) inventory management in supply chain, and 4) financial decisions in supply chain. The sequence of these themes helps transition from an enterprise-wide framework to network design to operational management to financial aspects of the supply chain. Each individual theme also addresses the answer to a challenging question as to how to go about applying quantitative tools to real-life operations, resulting in practical solutions. As the world moves toward more competitive and open markets, effective supply chain management is of critical importance to the success or failure of an enterprise. Despite a large amount of research achieved in the past decades on the supply chain management topic, many researchers and practitioners are still devoting considerable efforts on the emerging new problems. Designed to give you a collection of topics that bridge the gap between the academic arena and industrial practice, the book supplies a contemporary and up-to-date review on the advanced theory, applications, and practices of supply chain management, making it a rich resource for the design, analysis, and implementation of supply chain management problems arising in a wide range of industries.
This book presents a selection of recently developed collective and computational intelligence techniques, which it subsequently applies to energy management problems ranging from performance analysis to economic analysis, and from strategic analysis to operational analysis, with didactic numerical examples. As a form of intelligence emerging from the collaboration and competition of individuals, collective and computational intelligence addresses new methodological, theoretical, and practical aspects of complex energy management problems. The book offers an excellent reference guide for practitioners, researchers, lecturers and postgraduate students pursuing research on intelligence in energy management. The contributing authors are recognized researchers in the energy research field.