Using simplified notation and revealing unifying concepts, this book covers flow shop systems including two-machine, flexible and stochastic, and examines the reentrant flow shop, in which a job may be reprocessed at the same station or sequence of stations.

Although several monographs and edited volumes have discussed scheduling in general, most of these works survey the field by contributing a single chapter to production systems like flow shops. Flow Shop Scheduling: Theoretical Results, Algorithms, and Applications is solely dedicated to bringing together a huge body of knowledge on the subject, along distinct design features, in order to help scholars and practitioners easily identify problems of interest. This monograph has been organized into ten distinct flow shop systems and explores their connections. The chapters cover flow shop systems including two-machine, flexible, stochastic, and more. Outside of the traditional flow shops that require a job never revisits any stage, this book also examines the reentrant flow shop, in which a job may cycle back and be reprocessed at the same station or sequence of stations, multiple times. The authors have made the material accessible to a broad readership, using simplified notation and revealing unifying concepts. The results unique to flow shop research should provide the seed for research in other areas of scheduling and in optimization in general.

Although several monographs and edited volumes have discussed scheduling in general, most of these works survey the field by contributing a single chapter to production systems like flow shops. Flow Shop Scheduling: Theoretical Results, Algorithms, and Applications is solely dedicated to bringing together a huge body of knowledge on the subject, along distinct design features, in order to help scholars and practitioners easily identify problems of interest. This monograph has been organized into ten distinct flow shop systems and explores their connections. The chapters cover flow shop systems including two-machine, flexible, stochastic, and more. Outside of the traditional flow shops that require a job never revisits any stage, this book also examines the reentrant flow shop, in which a job may cycle back and be reprocessed at the same station or sequence of stations, multiple times. The authors have made the material accessible to a broad readership, using simplified notation and revealing unifying concepts. The results unique to flow shop research should provide the seed for research in other areas of scheduling and in optimization in general.

The book proposes new technologies and discusses future solutions for ICT design infrastructures, and includes high-quality submissions presented at the Third International Conference on ICT for Sustainable Development (ICT4SD 2018), held in Goa, India on 30–31 August 2018. The conference stimulated cutting-edge research discussions among pioneering researchers, scientists, industrial engineers, and students from all around the world. Bringing together experts from different countries, the book focuses on innovative issues at an international level.

This book discusses the process of "Lot Streaming" and how it can significantly improve the overall performance of a production process, and thereby, make the operation of a manufacturing system lean. It provides a complete introduction to the Flow Shop Lot Streaming Problem and provides a historical perspective. It further presents algorithms for a variety of lot streaming problems with numerical illustrations for ease of understanding and implementation.

This book provides an in-depth presentation of algorithms for and complexity of open shop scheduling. Open shops allow operations of a job to be executed in any order, contrary to flow and job shops where the order is pre-specified. The author brings the field up to date with more emphasis on new and recent results, and connections with graph edge coloring and mathematical programming. The book explores applications to production and operations management, wireless network scheduling, and timetabling. The book is addressed to researchers, graduate students, and practitioners in Operations Research, Operations Management, computer science and mathematics, who are developing and using mathematical approaches to applications in manufacturing, services and distributed wireless network scheduling.

Scheduling theory has received a growing interest since its origins in the second half of the 20th century. Developed initially for the study of scheduling problems with a single objective, the theory has been recently extended to problems involving multiple criteria. However, this extension has still left a gap between the classical multi-criteria approaches and some real-life problems in which not all jobs contribute to the evaluation of each criterion. In this book, we close this gap by presenting and developing multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. Several scenarios are introduced, depending on the definition and the intersection structure of the job subsets. Complexity results, approximation schemes, heuristics and exact algorithms are discussed for single-machine and parallel-machine scheduling environments. Definitions and algorithms are illustrated with the help of examples and figures.

This book provides a theoretical and application-oriented analysis of deterministic scheduling problems in advanced planning and computer systems. The text examines scheduling problems across a range of parameters: job priority, release times, due dates, processing times, precedence constraints, resource usage and more, focusing on such topics as computer systems and supply chain management. Discussion includes single and parallel processors, flexible shops and manufacturing systems, and resource-constrained project scheduling. Many applications from industry and service operations management and case studies are described. The handbook will be useful to a broad audience, from researchers to practitioners, graduate and advanced undergraduate students.

This book features the outcomes of the 9th International Conference on Soft Computing for Problem Solving, SocProS 2019, which brought together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to identify potential future directions. The book presents the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers in areas such as algorithms (artificial immune systems, artificial neural networks, genetic algorithms, genetic programming, and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). It is a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems that cannot easily be solved using traditional methods.

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2019), which was held at Technische Universität Dresden, Germany, on September 4-6, 2019, and was jointly organized by the German Operations Research Society (GOR) the Austrian Operations Research Society (ÖGOR), and the Swiss Operational Research Society (SOR/ASRO). More than 600 scientists, practitioners and students from mathematics, computer science, business/economics and related fields attended the conference and presented more than 400 papers in plenary presentations, parallel topic streams, as well as special award sessions. The respective papers discuss classical mathematical optimization, statistics and simulation techniques. These are complemented by computer science methods, and by tools for processing data, designing and implementing information systems. The book also examines recent advances in information technology, which allow big data volumes to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it includes problems modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc.