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.

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.

Statistical analysis of stock markets and foreign exchange markets has demonstrated the intermittent nature of economic time series. A nonlinear model of business cycles is able to simulate intermittency arising from order-chaos and chaos-chaos transitions. This monograph introduces new concepts of unstable periodic orbits and chaotic saddles, which are unstable structures embedded in a chaotic attractor and responsible for economic intermittency.

Agent-based Computational Economics (ACE) is a new discipline of economics, largely grounded on concepts like evolution, auto-organisation and emergence: it intensively uses computer simulations as well as artificial intelligence, mostly based on multi-agents systems. The purpose of this book is to give an up-to date view of the scientific production in the fields of Agent-based Computational Economics (mainly in Market Finance and Game Theory). Based on communications given at AE'2005 (Lille, USTL, France), this book offers a wide panorama of recent advances in ACE (both theoretical and methodological) that will interest academics as well as practitioners.

This work uses various model frameworks to study the evolution of equilibria in an open loop evolving economy in which the model characteristics evolve without any directional restrictions except for continuity. Applying mathematical methods, it is shown that equilibria can always be adapted in a piecewise gradual, non bang-bang way.

The book contains invited papers by well-known experts on a wide range of topics (economics, variational analysis, probability etc.) closely related to convexity and generalized convexity, and refereed contributions of specialists from the world on current research on generalized convexity and applications, in particular, to optimization, economics and operations research.

This volume features contributions to agent-based computational modeling from the social sciences and computer sciences. It presents applications of methodologies and tools, focusing on the uses, requirements, and constraints of agent-based models used by social scientists. Topics include agent-based macroeconomics, the emergence of norms and conventions, the dynamics of social and economic networks, and behavioral models in financial markets.