Our rapidly changing world has forced business practitioners, in corporation with academic researchers, to respond quickly and develop effective solution methodologies and techniques to handle new challenges in supply chain systems. Supply Chain Optimization, Management and Integration: Emerging Applications presents readers with a rich collection of ideas from researchers who are bridging the gap between the latest in information technology and supply chain management. This book includes theoretical, analytical, and empirical research, comprehensive reviews of relevant research, and case studies of effective applications in the field of SCM. The use of new technologies, methods, and techniques are emphasized by those who have worked with supply chain management across the world for those in the field of information systems.

Computational Intelligence (CI) is a term corresponding to a new generation of algorithmic methodologies in artificial intelligence, which combines elements of learning, adaptation, evolution and approximate (fuzzy) reasoning to create programs that can be considered intelligent. Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods presents computational intelligence methods for addressing supply chain issues. Emphasis is given to techniques that provide effective solutions to complex supply chain problems and exhibit superior performance to other methods of operations research.

Maritime Supply Chains breaks the maritime chain into components, consistently relating them to the overall integrated supply chain. The book not only analyzes and provides solutions to frequently encountered problems and key operational issues, it also applies cutting-edge scientific techniques on the maritime supply chain. Sections consider shipping, ports and terminals, hinterland and the issues that intersect different parts of the chain. Readers will find discussions of the various actors at play and how they relate to the overall function of the supply chain. Finally, the book offers solutions to the most pressing problems, thus providing a unique, well-balanced account. - Provides a comprehensive and integrative account of the maritime supply chain, from shipping, to port, to hinterland - Cuts through the maritime supply chain to offer a transversal picture on how the chain functions - Applies rigorous analytical techniques to give solutions to the most frequent and pressing challenges facing maritime supply chains - Considers advances, such as blockchain, that are set to transform maritime supply chains

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment.

In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition, multi-tree decomposition, Van Roy’ cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming. Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management. Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems.

Introduction and basic building blocks. Adding costs to two echelon supply chains. Advanced modeling and expanding to multiple echelons. How to get industrial streng results. Case study wrap up.

This research contribution presents the Reactive Disaster and supply chain Risk decision Support System ReDRiSS which supports decision-makers of logistical disaster management in the immediate aftermath of a supply chain disturbance. ReDRiSS suggests a methodology which combines approaches from scenario techniques, operations research and decision theory. Two case studies are provided which focus on decision situations of humanitarian logistics and of business continuity management.

Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.

This book presents real-world decision support systems, i.e., systems that have been running for some time and as such have been tested in real environments and complex situations; the cases are from various application domains and highlight the best practices in each stage of the system’s life cycle, from the initial requirements analysis and design phases to the final stages of the project. Each chapter provides decision-makers with recommendations and insights into lessons learned so that failures can be avoided and successes repeated. For this reason unsuccessful cases, which at some point of their life cycle were deemed as failures for one reason or another, are also included. All decision support systems are presented in a constructive, coherent and deductive manner to enhance the learning effect. It complements the many works that focus on theoretical aspects or individual module design and development by offering ‘good’ and ‘bad’ practices when developing and using decision support systems. Combining high-quality research with real-world implementations, it is of interest to researchers and professionals in industry alike.