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.
Written by a panel of leading international researchers, this Handbook identifies the key topics for research in supply chain management using an innovative step-by-step approach and provides an extensive range of methodologies for researching the subjects.
The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".
For reseach in all subjects and among different philisopical paradigms, research methodologies form one of the key issues to rely on. This volume brings a series of papers together, which present different research methodologies as applied in supply chain management. This comprises review oriented papers that look at what kind of methodologies have been applied, as well as methodological papers discussing new developments needed to successfully conduct research in supply chain management. The third group is made up of applications of the respective methodologies, which serve as examples on how the different methodological approaches can be applied. All papers have undergone a review process to ensure their quality. Therefore, we hope that this book will serve as a valid source for current and future researchers in the field. While the workshop on “Research Methodologies in Supply Chain Management” took place at the Supply Chain Management Center, Carl von Ossietzky Univ- sity in Oldenburg, Germany, it is based on a collaboration with the Supply Chain Management Group of the Department of Operations Management at the Cop- hagen Business School and the Department of Production Management at the Vienna University of Economics and Business Administration. We would like to thank all those who contributed to the workshop and this book.
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.
The 29th European Symposium on Computer Aided Process Engineering, contains the papers presented at the 29th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Eindhoven, The Netherlands, from June 16-19, 2019. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. - Presents findings and discussions from the 29th European Symposium of Computer Aided Process Engineering (ESCAPE) event
This book and its companion volumes, LNCS vols. 5551, 5552 and 5553, constitute the proceedings of the 6th International Symposium on Neural Networks (ISNN 2009), held during May 26–29, 2009 in Wuhan, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural n- works and related fields, with a successful sequence of ISNN symposia held in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), and Beijing (2008). Following the tradition of the ISNN series, ISNN 2009 provided a high-level inter- tional forum for scientists, engineers, and educators to present state-of-the-art research in neural networks and related fields, and also to discuss with international colleagues on the major opportunities and challenges for future neural network research. Over the past decades, the neural network community has witnessed tremendous - forts and developments in all aspects of neural network research, including theoretical foundations, architectures and network organizations, modeling and simulation, - pirical study, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, have provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large-scale, and n- worked brain-like intelligent systems. This long-term goal can only be achieved with the continuous efforts of the community to seriously investigate different issues of the neural networks and related fields.
A comprehensive, one-stop reference for cutting-edge research in integrated risk management, modern applications, and best practices In the field of business, the ever-growing dependency on global supply chains has created new challenges that traditional risk management must be equipped to handle. Handbook of Integrated Risk Management in Global Supply Chains uses a multi-disciplinary approach to present an effective way to manage complex, diverse, and interconnected global supply chain risks. Contributions from leading academics and researchers provide an action-based framework that captures real issues, implementation challenges, and concepts emerging from industry studies.The handbook is divided into five parts: Foundations and Overview introduces risk management and discusses the impact of supply chain disruptions on corporate performance Integrated Risk Management: Operations and Finance Interface explores the joint use of operational and financial hedging of commodity price uncertainties Supply Chain Finance discusses financing alternatives and the role of financial services in procurement contracts; inventory management and capital structure; and bank financing of inventories Operational Risk Management Strategies outlines supply risks and challenges in decentralized supply chains, such as competition and misalignment of incentives between buyers and suppliers Industrial Applications presents examples and case studies that showcase the discussed methodologies Each topic's presentation includes an introduction, key theories, formulas, and applications. Discussions conclude with a summary of the main concepts, a real-world example, and professional insights into common challenges and best practices. Handbook of Integrated Risk Management in Global Supply Chains is an essential reference for academics and practitioners in the areas of supply chain management, global logistics, management science, and industrial engineering who gather, analyze, and draw results from data. The handbook is also a suitable supplement for operations research, risk management, and financial engineering courses at the upper-undergraduate and graduate levels.
Risk management has become an essential issue in supply chain management, from the modeling of the decision maker's risk preference, and the studies on uncertain elements such as demand, supply, price, lead time, etc., to the consideration of more practical background including cash flow constraints, inventory financing and delayed cash payment. In this new volume, the authors provide a framework to study the interaction of various factors related to risk and their influence on supply chain management. The scope of areas covered includes operations management, decision analysis, and business administration. This book focuses on several key issues of risk management in supply chains. Specifically, an analysis framework is presented for studying the supplier selection problem and identifying the optimal sourcing strategy in a one-retailer two-suppliers supply chain with random yields. The optimal sourcing strategy of a retailer and the pricing strategies of two suppliers under an environment of supply disruption are investigated. Besides, the authors study the dynamic inventory control problems with cash flow constraints, financing decisions as well as delayed cash payment. In addition, originating from the annual international iron ore price negotiation, the authors model the bargaining process to deal with the risk of wholesale price in the game analysis context. Within the three perspectives of risk management in supply chains, the modeling of decision maker's risk preference has been extensively studied and many results have been obtained to guide the practice. However, the analysis on the other two kinds of topics is still in its infancy, and needs more efforts from academia. It is thus the ambition and innovation for this book to contribute on risk management in supply chains in the following ways: (1) characterizing the explicit sourcing strategy (i.e., single sourcing or dual sourcing) to deal with supply disruption risk; (2) introducing the concepts of financial risk measurement by incorporating cash flow constraints, inventory financing and delayed cash payment into inventory management models; and (3) providing insights for the iron ore price negotiation to help steel manufacturers handle the risk of price increase.
Efficient supply chain management is essential for maintaining successful workflows within companies. A lack of decisional, organizational, and information integration can lead to increased cost for a business due to missed opportunities, delays, inefficient inventory decisions, poor capacity allocation, and misuse of resources. Companies must employ collaborative practices across all functions of the supply chain in order to avoid costly mishaps. Hierarchical Planning and Information Sharing Techniques in Supply Chain Management is an essential reference source that discusses information exchanges and approaches of coordination related to operation planning for a better understanding of how hierarchical planning techniques and principles can contribute to the effective and efficient management and planning of supply chain activities. Featuring research on topics such as competitive advantages, information sharing, and transport management, this book is ideally designed for managers, academicians, and practitioners in the field of supply chain management, operations management, logistics, and operations research.
