This book studies air cargo capacity control problems. The focus is on analyzing decision models with intuitive optimal decisions as well as on developing efficient heuristics and bounds. Three different models are studied: First, a model for steering the availability of cargo space on single legs. Second, a model that simultaneously optimizes the availability of both seats and cargo capacity. Third, a decision model that controls the availability of cargo capacity on a network of flights.

This book constitutes revised selected papers from the 7th International Conference on Operations Research and Enterprise Systems, ICORES 2018, held in Funchal, Madeira, Portugal, in January 2018. The 12 papers presented in this volume were carefully reviewed and selected from a total of 59 submissions. They are organized in topical sections named: methodologies and technologies; and applications.

Revenue management (RM) has emerged as one of the most important new business practices in recent times. This book is the first comprehensive reference book to be published in the field of RM. It unifies the field, drawing from industry sources as well as relevant research from disparate disciplines, as well as documenting industry practices and implementation details. Successful hardcover version published in April 2004.

This book uses numerous examples to describe the current opportunities and risks of air freight against the backdrop of stagnating transport volumes since the financial crisis in 2008. It shows what impact these developments have had on those involved, in particular shippers, airlines, airports and freight forwarders. The application-oriented presentation also provides an insight into the design of complex supply chains and the areas of tension in which the players in air freight operate.

This is the Proceedings of the Eighth International Conference on Management Science and Engineering Management (ICMSEM) held from July 25 to 27, 2014 at Universidade Nova de Lisboa, Lisbon, Portugal and organized by International Society of Management Science and Engineering Management (ISMSEM), Sichuan University (Chengdu, China) and Universidade Nova de Lisboa (Lisbon, Portugal). The goals of the conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current findings. A total number of 138 papers from 14 countries are selected for the proceedings by the conference scientific committee through rigorous referee review. The selected papers in the first volume are focused on Intelligent System and Management Science covering areas of Intelligent Systems, Decision Support Systems, Manufacturing and Supply Chain Management.

This book proposes capacity options as a flexible alternative air cargo contract type, and illustrates how capacity can be priced through option contracts. The analysis is accomplished by means of an analytical multivariate optimization model under price and demand uncertainty. A case study using data from a leading German carrier illustrates the financial potential. Finally, the author shows how capacity-option contracts integrate into the context of air cargo revenue management.

From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.

This book presents recent research in intelligent and fuzzy techniques on digital transformation and the new normal, the state to which economies, societies, etc. settle following a crisis bringing us to a new environment. Digital transformation and the new normal-appearing in many areas such as digital economy, digital finance, digital government, digital health, and digital education are the main scope of this book. The readers can benefit from this book for preparing for a digital “new normal” and maintaining a leadership position among competitors in both manufacturing and service companies. Digitizing an industrial company is a challenging process, which involves rethinking established structures, processes, and steering mechanisms presented in this book. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying digital transformation and new normal. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.

​A major problem arising in airline alliances is to design allocation mechanisms determining how the revenue of a product should be shared among the airlines. The nucleolus is a concept of cooperative game theory that provides solutions for allocating the cost or benefit of a cooperation. This work provides fair revenue proportions for the airline alliances based on the nucleolus, which assumes a centralized decision making system. The proposed mechanism is used as a benchmark to evaluate the fairness of the revenue sharing mechanisms, where the alliance partners behave selfishly. Additionally, a new selfish revenue allocation rule is developed that improves the performance of the existing methods.