Bøger i International Series in Operations Research & Management Science serien

This handbook includes contributions related to optimization, pricing and valuation problems, risk modeling and decision making problems arising in global financial and commodity markets from the perspective of Operations Research and Management Science. The book is structured in three parts, emphasizing common methodological approaches arising in the areas of interest: -          Part I: Optimization techniques -          Part II: Pricing and Valuation -          Part III: Risk Modeling The book presents to a wide community of Academics and Practitioners a selection of theoretical and applied contributions on topics that have recently attracted increasing interest in commodity and financial markets. Within a structure based on the three parts, it presents recent state-of-the-art and original works related to: -          The adoption of multi-criteria and dynamic optimization approaches in financial and insurance markets in presence of market stress and growing systemic risk; -          Decision paradigms, based on behavioral finance or factor-based, or more classical stochastic optimization techniques, applied to portfolio selection problems including new asset classes such as alternative investments; -          Risk measurement methodologies, including model risk assessment, recently applied to energy spot and future markets and new risk measures recently proposed to evaluate risk-reward trade-offs in global financial and commodity markets; and derivatives portfolio hedging and pricing methods recently put forward in the financial community in the aftermath of the global financial crisis.

This book focuses on optimal control and systems engineering in the big data era. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications.

This book is an expository introduction to the methodology of sensitivity analysis of model output.

This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used in the area of Banking and Finance.

This book grows from a conference on the state of the art and recent advances in Efficiency and Productivity. Papers were commissioned from leading researchers in the field, and include eight explorations into the analytical foundations of efficiency and productivity analysis. Chapters on modeling advances include reverse directional distance function, a new method for estimating technological production possibilities, a new distance function called a loss distance function, an analysis of productivity and price recovery indices, the relation of technical efficiency measures to productivity measures, the implications for benchmarking and target setting of imposing weight restrictions on DEA models, weight restrictions in a regulatory setting, and the Principle of Least Action.Chapters on empirical applications include a study of innovative firms that use innovation inputs to produce innovation outputs, a study of the impact of potential ¿coopetition¿ or cooperation among competitors on the financial performance of European automobile plants, using SFA to estimate the eco-efficiency of dairy farms in Spain, a DEA bankruptcy prediction model, a combined stochastic cost frontier analysis model/mixture hazard model, the evolution of energy intensity in nine Spanish manufacturing industries, and the productivity of US farmers as they age.

This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows users to develop and formally support approximate and simple decision rules, and this book showcases state-of-the-art applications in which MDP was key to the solution approach.

This book deals with complex problems in the fields of logistics and supply chain management and discusses advanced methods, especially from the field of computational intelligence (CI), for solving them.

This book begins with a review of basic results in optimal search for a stationary target. Next it develops methods for computing optimal search plans involving multiple targets and multiple searchers with realistic operational constraints on search movement.

Problems with multiple objectives and criteria are generally known as multiple criteria optimization or multiple criteria decision-making (MCDM) problems.

This text addresses the modeling of scenarios in virtually every combat area including shooting without feedback, shooting with feedback, target defense, attrition models, game theory and wargames, search, unmanned aerial vehicles, and terror and insurgency.

Project scheduling problems are, generally speaking, the problems of allocating scarce resources over time to perform a given set of activities. ), Advances in Project Scheduling, Elsevier, 1989, summarizing the state-of-the-art across project scheduling problems, was published.

Equilibrium is a concept used in operations research and economics to understand the interplay of factors and problems arising from competitive systems in the economic world. new mathematical methods allowing researchers to combine other theoretical approaches with the projected dynamical systems approach;

4th Party Cyber Logistics For Air Cargo is a technical discussion for researchers and practitioners to understand the issues, models, and future directions of air cargo logistics in the cyber era.

Learning plays a fundamental role in the production planning and growth of all organizations. Human Learning:From Learning Curves to Learning Organizations covers a broad range of learning models and related topics beginning with learning curves to recent research on learning organizations.

The use of evolutionary computation techniques has grown considerably. The use and applications of these techniques have been further enhanced resulting in a set of computational intelligence tools that are adept for solving complex optimization problems. This book covers the foundation as well as the practical side of evolutionary optimization.

Sample-Path Analysis of Queueing Systems uses a deterministic (sample-path) approach to analyze stochastic systems, primarily queueing systems and more general input-output systems.

An Annotated Timeline of Operations Research: An Informal History recounts the evolution of Operations Research (OR) as a new science - the science of decision making.

Other goals are to edit the known results in a unified manner, classify them and identify where and how they relate to each other, and fill in some gaps with new results. we have highlighted the results For each topic covered in the book, that, in our opinion, are the most important.

The generalized area of multiple criteria decision making (MCDM) can be defined as the body of methods and procedures by which the concern for multiple conflicting criteria can be formally incorporated into the analytical process.

This book is focused on the impact of ocean transport logistics on global supply chains. Finally Part III explores at shippers and global supply chain management, with chapters on transportation service procurement, hinterland transportation, green corridors, as well as competition and co-operation in maritime logistics operations.

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.

The Handbook is a comprehensive research reference that is essential for anyone interested in conducting research in supply chain.

This is a systematic, state-of-the-art treatment of military operations research (MOR). It examines issues that relate to both tactical and strategic levels. Several examples have been solved in each chapter to illustrate the application of the techniques of MOR to military systems.

This book offers complete coverage of logistics, examining modes, general issues, logistics in specific regions, free-trade zones, innovations in international logistics, case studies and a look at the future.

In a straightforward and approachable manner, this book introduces complementarity models, and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques.

1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming-studiessequential optimization ofdiscrete time stochastic systems.

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics.

This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of ¿productivity analysis/data envelopment analysis¿ and ¿data science/big datä. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others.Examples of data science techniques include linear and logistic regressions, decision trees, Naïve Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubt that nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data.Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.

This book constructs a model of the knowledge value chain in the university and analyzes the university knowledge value-added mechanism in the process of Industry-University Collaborative Innovation.