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The book considers the lot-sizing and scheduling problem for flexible flow line production facilities. Flexible flow lines are flow lines with parallel machines on some or all production stages. They can be found in a vast number of industries. A three-phased solution approach is presented that solves the integrated lot-sizing and scheduling problem in a hierarchical manner. The approach is able to handle several important features relevant in industrial practice, such as back-orders and setup carry-over. The developed solution procedures solve practically sized problems in a relatively short amount of time. One of the procedures is based on a novel mixed integer programming (MIP) model, which employs integer variables instead of binary variables. This makes it possible to find (near-)optimal solutions using standard algorithms such as CPLEX. Another procedure uses two nested Genetic Algorithms. An application of the framework in the semiconductor industry is given.
This volume contains a selection of 128 papers presented in lectures during the international scientific symposium "Operations Research 2005" (OR 2005) held at the University of Bremen, September 7-9, 2005. This international conference took place under the auspices of the German Operations Research Society (GOR). The symposium had about 600 participants from countries all over the world. It attracted academics and practitioners working in various fields of Operations Research and provided them with the most recent advances in Operations Research as well as related areas in Economics, Mathematics, and Computer Science including the special interest streams Logistics and New Maritime Businesses. The program consisted of 3 plenary and 15 semi-plenary talks and about 400 contributed presentations selected by the program committee to be presented in 20 sections.
​Due to a varying product demand (changing product mix) and different production speeds, bottlenecks may shift between the stages. In that case, a simultaneous lot-sizing and scheduling of these stages is recommendable. Hence, an improved version of the General Lot-Sizing and Scheduling Problem for Multiple production Stages (GLSPMS) was developed. Moreover, several reformulation techniques were applied to this model to solve it exactly. Besides, a new meta-heuristic which combines the principles of Variable Neighborhood Decomposition Search (VNDS) and Exchange was implemented to find good solutions, even for a real-world problem case. Finally, further model extensions, e.g., for scarce setup resources, were proposed.
The book at hand presents a careful selection of relevant applications of CI methods for transport, logistics, and supply chain management problems. The chapters illustrate the current state-of-the-art in the application of CI methods in these fields and should help and inspire researchers and practitioners to apply and develop efficient methods. A few contributions in this book are extended versions of papers presented at EvoTransLog2007: The First European Workshop on Evolutionary Computation in Transportation and Logistics which was held in Valencia, Spain, in 2007. The majority of contributions are from additional, specially selected researchers, who have done relevant work in different areas of transport, logistics, and supply chain management. The goal is to broadly cover representative applications in these fields as well as different types of solution approaches. On the application side, the contributions focus on design of traffic and transportation networks, vehicle routing, and other important aspects of supply chain management such as inventory management, lot sizing, and lot scheduling. On the method side, the contributions deal with evolutionary algorithms, local search approaches, and scatter search combined with other CI techniques such as neural networks or fuzzy approaches. The book is structured according to the application domains. Thus, it has three parts dealing with traffic and transportation networks, vehicle routing, and supply chain management.
This book presents the proceedings of the 4th Asia Pacific Conference on Manufacturing Systems and International Manufacturing Engineering Conference (APCOMS-IMEC 2022), held in Surakarta, Indonesia, on 27 October 2022. The book presented selected papers covering scientific research in the field of manufacturing engineering, with focuses on industrial engineering, materials, and processes. The book appeals to researchers, academics, scientists, students, engineers, and practitioners who are interested in the latest developments and applications related to manufacturing engineering.
Information Control Problems in Manufacturing 2006 contains the Proceedings of the 12th IFAC Symposium on Information Control Problems in Manufacturing (INCOM'2006). This symposium took place in Saint Etienne, France, on May 17-19 2006. INCOM is a tri-annual event of symposia series organized by IFAC and it is promoted by the IFAC Technical Committee on Manufacturing Plant Control. The purpose of the symposium INCOM'2006 was to offer a forum to present the state-of-the-art in international research and development work, with special emphasis on the applications of optimisation methods, automation and IT technologies in the control of manufacturing plants and the entire supply chain within the enterprise. The symposium stressed the scientific challenges and issues, covering the whole product and processes life cycle, from the design through the manufacturing and maintenance, to the distribution and service. INCOM'2006 Technical Program also included a special event on Innovative Engineering Techniques in Healthcare Delivery. The application of engineering and IT methods in medicine is a rapidly growing field with many opportunities for innovation. The Proceedings are composed of 3 volumes: Volume 1 - Information Systems, Control & Interoperability Volume 2 - Industrial Engineering Volume 3 - Operational Research * 3-volume set, containing 362 carefully reviewed and selected papers * presenting the state-of-the-art in international research and development in Information Control problems in Manufacturing
This book is a guide to modern production planning methods based on new scientific achievements and various practical planning rules of thumb. Several numerical examples illustrate most of the calculation methods, while the text includes a set of programs for calculating production schedules and an example of a cloud-based enterprise resource planning (ERP) system. Despite the relatively large number of books dedicated to this topic, Advanced Planning and Scheduling is the first book of its kind to feature such a wide range of information in a single work, a fact that inspired the author to write this book and publish an English translation. This work consists of two parts, with the first part addressing the design of reference and mathematical models, bottleneck models and multi-criteria models and presenting various sample models. It describes demand-forecasting methods and also includes considerations for aggregating forecasts. Lastly, it provides reference information on methods for data stocking and sorting. The second part of the book analyzes various stock planning models and the rules of safety stock calculation, while also considering the stock traffic dynamics in supply chains. Various batch computation methods are described in detail, while production planning is considered on several levels, including supply planning for customers, master planning, and production scheduling. This book can be used as a reference and manual for current planning methods. It is aimed at production planning department managers, company information system specialists, as well as scientists and PhD students conducting research in production planning. It will also be a valuable resource for students at universities of applied sciences.
Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering
Lotsizing problems are found in every company, which produces various items on resources with scarce capacities. In general, the objective is to find production plans, which meet demand with the resources` given capacities and at minimal costs. However, there is a great variety of company-specific lotsizing problems due to the complexity of the underlying production processes. Both standard MRP-systems and modern Advanced Planning Systems fail to provide adequate solutions. Instead, they most often compute production plans, which are not feasible in practice. In this book new lotsizing models are presented for multi-stage production systems with general product structures, dynamic demand, setup times and lead times. They are extended to cover production on parallel machines. An iterative solution procedure is presented, which generates feasible production plans within seconds of computation time. Potential readership includes scholars of supply chain management and production planning, interested students in these areas as well as practitioners involved in production planning.
Arti?cial Intelligence is a ?eld with a long history, which is still very much active and developing today. Developments of new and improved techniques, together with the ever-increasing levels of available computing resources, are fueling an increasing spread of AI applications. These applications, as well as providing the economic rationale for the research, also provide the impetus to further improve the performance of our techniques. This further improvement today is most likely to come from an understanding of the ways our systems work, and therefore of their limitations, rather than from ideas ‘borrowed’ from biology. From this understanding comes improvement; from improvement comes further application; from further application comes the opportunity to further understand the limitations, and so the cycle repeats itself inde?nitely. In this volume are papers on a wide range of topics; some describe appli- tions that are only possible as a result of recent developments, others describe new developments only just being moved into practical application. All the - pers re?ect the way this ?eld continues to drive forward. This conference is the 15th in an unbroken series of annual conferences on Industrial and Engineering Application of Arti?cial Intelligence and Expert Systems organized under the auspices of the International Society of Applied Intelligence.