Bøger i Uncertainty and Operations Res serien

This book focuses on selected aspects of the current and upcoming trends in transportation, logistics and decision making. In detail the included transportation management, optimization and management of logistics system, big data technology and method, financial engineering and risk management, investment decision and risk management, data-driven process management decision, scheduling optimization and combination decision, theory and method of forecasting and decision making, data mining and knowledge management, operation and green supply chain management, industrial engineering and operation management, information system and business intelligence, Internet + green manufacturing, strategic emerging industries and Industrial finance, big data and smart city. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of International Conference on Intelligent Transportation and Logistics with Big Data & International Forum onDecision Sciences, which took place in Harbin, Heilongjiang province, China, in 2022.

This book aims at providing cases with inspiring findings for global researchers in capacity allocation and reservation. Capacity allocation mechanisms are introduced in the book, as well as the measures to build models and the ways to achieve supply chain coordination. In addition, it illustrates the capacity reservation contract and quantity flexible contract with comparisons and some numerical studies. The book is divided into 7 chapters. Chapter 1 introduces the background and the latest development of the research. Chapter 2 introduces how to manage downstream competition through capacity allocation in symmetric market, including proportional mechanism and lexicographic mechanism. Demand competition is introduced in Chapter 3 as well as the uniform allocation mechanism and the comparisons among three different mechanisms. In Chapter 4, we give information about demand competition with fixed factor allocation, and the comparison with other allocations. Chapter 5 provides the optimal strategies under fixed allocation with multiple retailers and the impacts of fixed proportions. Chapter 6 illustrates how to achieve supply chain coordination through capacity reservation contract and its comparison with the quantity flexibility contract, and in Chapter 7 we describe outsourcing decisions and order policies in different systems with some numerical studies. We sincerely hope that this book can provide some useful suggestions and inspirations for scholars around the world who have the same interests in this field. 

This book focuses on the following three key topics in social network large-scale decision-making: structure-heterogeneous information fusion, clustering analysis with multiple measurement attributes, and consensus building considering trust loss. To address the aggregation and distance measurement of structure-heterogeneous evaluation information, we propose a fusion method based on trust and behavior analysis. Then, two clustering algorithms are put forward, including trust Cop-K-means clustering algorithm and compatibility distance-oriented off-center clustering algorithm. The above clustering algorithms emphasize the similarity of opinions and social relationships as important measurement attributes of clustering. Finally, this book explores the impact of trust loss originating from social relationships on the CRP and develops two consensus-reaching models, namely the improved minimum-cost consensus model that takes into account voluntary trust loss and the punishment-driven consensus-reaching model. Some case studies, a large number of numerical experiments, and comparative analyses are provided in this book to demonstrate the characteristics and advantages of the proposed methods and models. The authors encourage researchers, students, and enterprises engaged in social network analysis, group decision-making, multi-agent collaborative decision-making, and large-scale data processing to pay attention to the proposals presented in this book. After reading this book, the authors expect readers to have a deeper and more comprehensive understanding of social network large-scale decision-making. Inorder to make it more accurate for readers to understand the methods and models presented in this book, the authors strongly recommend that potential readers have a good research foundation in fuzzy soft computing, traditional clustering algorithms, basic mathematics knowledge, and other related preliminaries.