Traditional mathematical programming has concentrated on problems that can be solved by achieving a single objective. In reality, many multi-objective situations exist; concentrating on a single goal limits the applicability of math programming models. Accordingly, multiobjective optimization has emerged as a rapdily growing area. In this monograph the author draws from the more mature body of literature on multicriterion decision theory to enhance understanding of multiobjective optimization. There are obvious commonalities between the two areas, but to date no one has presented a book which unifies the two. That is the aim of "Multiobjective Optimization: Behavioural and Computational Considerations". There are many behavioural and computational issues which are relevant to multiobjective optimization. These issues cross the disciplines of behavioural decision theory, information and decision support systems, and computational analysis.

A logic view of 0-1 integer programming problems, providing new insights into the structure of problems that can lead the researcher to more effective solution techniques depending on the problem class. Operations research techniques are integrated into a logic programming environment. The first monographic treatment that begins to unify these two methodological approaches. Logic-based methods for modelling and solving combinatorial problems have recently started to play a significant role in both theory and practice. The application of logic to combinatorial problems has a dual aspect. On one hand, constraint logic programming allows one to declaratively model combinatorial problems over an appropriate constraint domain, the problems then being solved by a corresponding constraint solver. Besides being a high-level declarative interface to the constraint solver, the logic programming language allows one also to implement those subproblems that cannot be naturally expressed with constraints. On the other hand, logic-based methods can be used as a constraint solving technique within a constraint solver for combinatorial problems modelled as 0-1 integer programs.

This is the first book to examine the linkages among natural and organizational accidents and disasters in the modern era and clarifies the mechanisms involved and the significance of emerging problems, from the aging of vital infrastructure for the supply of water, gas, oil, and electricity to the breakdown of pensions, healthcare, and other social systems. The book demonstrates how we might check the underlying civilizational collapse and then explore translational systems approaches toward resilient management and policy for sustainability. In Unsafety, the author focuses on the kinds of unnatural disasters and organizational accidents that arise as repercussions of natural hazards. Japan serves as an example, where earthquakes, tsunamis, and typhoons are common, with the Fukushima nuclear disaster as an outstanding case of this link between natural disasters and organizational accidents. Natural and human-made disasters happen worldwide and cause misery through loss of life; destruction of livelihoods as in agriculture, fisheries, and the manufacturing industry; and interruption of urban life. Unsafety from a disaster in one place increases uncertainty elsewhere, presenting urgent issues in all nations for individuals, organizations, regions, and the state. The author explains that one factor in the Fukushima catastrophe, which followed in the wake of the earthquake and tsunami in 2011, was the latent deterioration and aging of systems at all levels from the physical to the social, leading through a chain reaction to unsought and unforeseen consequences. Here, the aging of the nuclear reactor system, the breakdown of safety management, and inappropriate instructions from the regulatory authorities combined to create the three-fold disaster, in which technological, organizational, and governmental dysfunction have been diagnosed as reflecting a "systems pathology" infecting all levels.

This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three chapters on how to measure the complexity of a search heuristic: black-box complexity, a counterpart of classical complexity theory in black-box optimization; parameterized complexity, aimed at a more fine-grained view of the difficulty of problems; and the fixed-budget perspective, which answers the question of how good a solution will be after investing a certain computational budget. The book then describes theoretical results on three important questions in evolutionary computation: how to profit from changing the parameters during the run of an algorithm; how evolutionary algorithms cope with dynamically changing or stochastic environments; and how population diversity influences performance. Finally, the book looks at three algorithm classes that have only recently become the focus of theoretical work: estimation-of-distribution algorithms; artificial immune systems; and genetic programming. Throughout the book the contributing authors try to develop an understanding for how these methods work, and why they are so successful in many applications. The book will be useful for students and researchers in theoretical computer science and evolutionary computing.

Project management can be broadly defined as the process of managing, allocating and timing resources to achieve given objectives in an efficient and expedient manner. The builders of the pyramids in Egypt and the Maya temples in Central America are often cited as the world's first project managers. Without the help of computers or planning software, they managed exceptionally complex projects, using the simplest of tools. Nowadays projects, sets of activities which have a defined start point and a defined end state and which pursue a defined goal and use a defined set of resources, come in many and various forms. The Manhattan project which created the first atom bomb, the Apollo moon program, the construction of the Channel tunnel, the design of the Airbus, the development of new products, the construction of large office buildings, the relocation of a factory, the installation of a new information system, as well as the development of a marketing plan are all well-known examples of projects.

Our objectives in writing Project Scheduling: A Research Handbook are threefold: (1) Provide a unified scheme for classifying the numerous project scheduling problems occurring in practice and studied in the literature; (2) Provide a unified and up-to-date treatment of the state-of-the-art procedures developed for their solution; (3) Alert the reader to various important problems that are still in need of considerable research effort. As such, this book should differ from other project scheduling books in its use of an innovative unified resource scheduling classification scheme, and a unified treatment of both exact and heuristic solution procedures.

Project Scheduling: A ResearchHandbook has been divided into four parts. Part I consists of three chapters on the scope and relevance of project scheduling, on the nature of project scheduling, and finally on the introduction of a unified scheme that will be used in subsequent chapters for the identification and classification of the project scheduling problems studied in this book. Part II focuses on the time analysis of project networks. Part III carries the discussion further into the crucial topic of scheduling under scarce resources. Part IV deals with robust scheduling and stochastic scheduling issues. Numerous tables and figures are used throughout the book to enhance the clarity and effectiveness of the discussions. For the interested and motivated reader, the problems at the end of each chapter should be considered as an integral part of the presentation.

Scheduling, planning and packing are ubiquitous problems that can be found in a wide range of real-world settings. These problems transpire in a large variety of forms, and have enormous socio-economic impact. For many years, significant work has been devoted to automating the processes of scheduling, planning and packing using different kinds of methods. However, poor scaling and the lack of flexibility of many of the conventional methods coupled with the fact that most of the real-world problems across the application areas of scheduling, planning and packing nowadays tend to be of large scale, dynamic and full of complex dependencies have made it necessary to tackle them in unconventional ways.

This volume, "Natural Intelligence for Scheduling, Planning and Packing Problems," is a collection of numerous natural intelligence based approaches for solving various kinds of scheduling, planning and packing problems. It comprises 12 chapters which present many methods that draw inspiration from nature, such as evolutionary algorithms, neural-fuzzy system, particle swarm algorithms, ant colony optimisation, extremal optimisation, raindrop optimisation, and so on. Problems addressed by these chapters include freight transportation, job shop scheduling, flowshop scheduling, electrical load forecasting, vehicle routing, two-dimensional strip packing, network configuration and forest planning, among others. Along with solving these problems, the contributing authors present a lively discussion of the various aspects of the nature-inspired algorithms utilised, providing very useful and important new insights into the research areas.

Information and Process Integration in Enterprises: Rethinking Documents is a bold attempt to address information and process integration issues as a single body of research and practice. This book has identified the concept of documents as a common thread linking the integration issues. Documents, after all, are representations of information, along with representations of the usage of the information contained therein. Rethinking the role of documents is therefore central to (re)engineering enterprises in the context of information and process integration. The chapters of this book are based on papers presented at the International Working Conference on Information and Process Integration in Enterprises (IPIC '96)', held at MIT on November 14 and 15, 1996. The chapters cover a range of issues: from the future role of documents in enterprise integration, to emerging models of business processes and information use, to practical experiences in implementing new processes and technologies in real work environments. Information and Process Integration in Enterprises: Rethinking Documents is suitable as a secondary text for a graduate level course on information technology.

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.

This edited volume captures and communicates the best thinking on how to improve healthcare by improving the delivery of services -- providing care when and where it is needed most -- through application of state-of-the-art scheduling systems. Over 12 chapters, the authors cover aspects of setting appointments, allocating healthcare resources, and planning to ensure that capacity matches needs for care. A central theme of the book is increasing healthcare efficiency so that both the cost of care is reduced and more patients have access to care. This can be accomplished through reduction of idle time, lessening the time needed to provide services and matching resources to the needs where they can have the greatest possible impact on health. Within their chapters, authors address: (1) Use of scheduling to improve healthcare efficiency. (2) Objectives, constraints and mathematical formulations. (3) Key methods and techniques for creating schedules. (4) Recent developments that improve the available problem solving methods. (5) Actual applications, demonstrating how the methods can be used. (6) Future directions in which the field of research is heading. Collectively, the chapters provide a comprehensive state-of-the-art review of models and methods for scheduling the delivery of patient care for all parts of the healthcare system. Chapter topics include setting appointments for ambulatory care and outpatient procedures, surgical scheduling, nurse scheduling, bed management and allocation, medical supply logistics and routing and scheduling for home healthcare.

Global logistics entails tradeoffs in facility location, distribution networks, the routing and scheduling of deliveries by different modes of travel (e.g., air, water, truck, rail), procurement, and the overall management of international supply chains. In an increasingly global economy, then, logistics has become a very important matter in the success or failure of an organization. It is an integral part of supply chain management that involves not just operations management considerations, but production engineering and regional science issues as well. As Director of the prestigious Waterloo Management of Integrated Manufacturing Systems Research Group (WATMIMS), which specializes in logistics and manufacturing, Jim Bookbinder is uniquely qualified to edit a handbook on global logistics. He has aligned a set of prominent contributors for this volume. The chapters in the Handbook are organized into discrete sections that examine modes; logistics in particular countries; operations within a free-trade zone; innovative features impacting international logistics; case studies of specific companies; and a look toward the future. Contributors are from the Americas, Europe, and Asia, and they push the state of the art in areas such as trade vs. security; border issues; cabotage within NAFTA; Green logistics corridors within the EU; inland ports; direct-to-store considerations; and all the questions that need to be confronted in any given region. This will certainly appeal to researchers and practitioners alike, and could serve as required or supplementary reading in graduate-level logistics courses as well.

This book presents for the first time a methodology that combines the power of a modelling formalism such as colored petri nets with the flexibility of a discrete event program such as SIMIO. Industrial practitioners have seen the growth of simulation as a methodology for tacking problems in which variability is the common denominator. Practically all industrial systems, from manufacturing to aviation are considered stochastic systems. Different modelling techniques have been developed as well as mathematical techniques for formalizing the cause-effect relationships in industrial and complex systems. The methodology in this book illustrates how complexity in modelling can be tackled by the use of coloured petri nets, while at the same time the variability present in systems is integrated in a robust fashion. The book can be used as a concise guide for developing robust models, which are able to efficiently simulate the cause-effect relationships present in complex industrial systems without losing the simulation power of discrete-event simulation. In addition SIMIO's capabilities allows integration of features that are becoming more and more important for the success of projects such as animation, virtual reality, and geographical information systems (GIS).

Postponement strategy is one of the major supply chain management (SCM) pr- tices that has a discernible impact on rms' competitive advantage and organi- tional performance. Postponement is a mass customization strategy that captures the advantages of both mass production and mass customization. Recent research studies have identi ed four common postponement strategies, namely pull, logistics, form and price postponement. The former three postponement strategies are linked to production and manufacturing, while the last one is a pure pricing strategy. They aim at balancing the costs and bene ts of mass production and mass customization. Practical examples of postponement can be found in the high-tech industry, food industry and other industries that require high differentiation. However, empirical studies have found that postponement may not be an evident SCM practice compared to the other practices. In addition, postponement has both positive and negative impacts on a supply chain. The advantages include following the JIT principles, reducing end-product inventory, making forecasting easier and pooling risk. The high cost of designing and manufacturing generic components is the main drawback of postponement. Thus, the evaluation of postponement strategy is an important research issue and there have been many qualitative and quantitative models for analyzing postponement under different scenarios.

Strategic Risk examines a fundamental issue in the field of strategic management and organizations: how to study changes in the competitive outcomes of firms. Collins and Ruefli develop the concept of ordinal risk and extend this concept and its associated measures to the more general framework of state-defined systems. The book makes the state-defined risk methodology more accessible to strategic management researchers, and to social scientists in general. The need for quantitative frameworks with which to analyze the dynamics of strategic management has been apparent for some time. The state-defined risk methodology has the advantage of being based on a common usage definition of risk, and is also based on a mathematically well-behaved function. It permits investigation of the chance of gain while yielding a measure of environmental uncertainty. Finally, the development is general and permits applications employing a variety of performance dimensions over a range of entities in a diversity of contexts. The authors demonstrate the practicability and reliability of this approach by applying the model to mutual funds, large mining and manufacturing firms, and public firms on an industry by industry basis.

The book focuses on applications of belief functions to business decisions. Section I introduces the intuitive, conceptual and historical development of belief functions. Three different interpretations (the marginally correct approximation, the qualitative model, and the quantitative model) of belief functions are investigated, and rough set theory and structured query language (SQL) are used to express belief function semantics. Section II presents applications of belief functions in information systems and auditing. Included are discussions on how a belief-function framework provides a more efficient and effective audit methodology and also the appropriateness of belief functions to represent uncertainties in audit evidence. The third section deals with applications of belief functions to mergers and acquisitions; financial analysis of engineering enterprises; forecast demand for mobile satellite services; modeling financial portfolios; and economics.

This book is a collection of essays in honor of John C. Harsanyi. Originally, we hoped that it would be ready in the year of his 70th birthday, but we did not quite succeed. It sometimes takes longer than anticipated to do things as well as one wants. I think that John Harsanyi will understand this. It is my desire to express our thanks to all those who helped to make the book possible, especially to the publishing house, the Springer Verlag. I am grateful to Hildegard Grober who assisted us in the organizational tasks connected to our editorial effort. I am deeply indebted to Horace W. Brock. His active support was extremely valuable. The results of my editorial efforts should partly be attributed to him. Reinhard Selten Table of Contents Introduction 1 I. Coopera. tive Game Theory The Consistent Shapley Value for Games without Side Payments by Michael Maschler and Guillermo Owen 5 Fictitious-Transfer Solutions in Cooperative Game Theory by Roger B. Myerson 13 The Finagle Point for Characteristic Function Games by Guillermo Owen 35 Voting by Count and Account by Bezalel Peleg 45 Fee Games: (N)TU-Games with Incomplete Information by Joachim Rosenmftller 53 A Non-Cooperative Interpretation of Value and Potential 83 by Sergiu Hart and Andreu Mas-Colell II.

The 1980s and 1990s have seen a growing interest in research and practice in the use of methodologies within problem contexts characterised by a primary focus on technology, human issues, or power. During the last five to ten years, this has given rise to challenges regarding the ability of a single methodology to address all such contexts, and the consequent development of approaches which aim to mix methodologies within a single problem situation. This has been particularly so where the situation has called for a mix of technological (the so-called 'hard') and human centred (so-called 'soft') methods. The approach developed has been termed mixed-mode modelling. The area of mixed-mode modelling is relatively new, with the phrase being coined approximately four years ago by Brian Lehaney in a keynote paper published at the 1996 Annual Conference of the UK Operational Research Society. Mixed-mode modelling, as suggested above, is a new way of considering problem situations faced by organisations. Traditional technological approaches used in management science have suffered criticisms relating to their adequacy in the past few decades, and these hard approaches have been replaced by soft methods, which consider process more relevant than outcome. However, the sole use of human centred approaches to organisational problems has also proved to be inadequate. Mixed-mode modelling accepts the importance of both process and outcome, and provides enabling mechanisms for hard and soft investigation to be undertaken."

This book presents a review of the role of overconfidence in small firms and explores how biased judgment and decision-making can affect business performance. Whilst the overconfidence construct has been studied in detail, there are no systematic reviews of its role in SMEs as of yet. Examining the decisions made by entrepreneurs, this study offers clear solutions on how to improve business accuracy, reduce disadvantageous investments and prevent bankruptcy. Providing an empirical analysis of overconfidence in the sport industry, this new book will not only be of interest to academics of entrepreneurship and small enterprises, but also to sport managers.

In this book methods from Operations Research and Game Theory are used to determine companies' profit-maximizing strategies related to pricing and (cooperative) advertising. It considers different supply chain structures as well as various distributions of power, making it possible to analyze both inter-echelon and intra-echelon dependencies between the companies' decisions. Additionally, an approach based on fuzzy set theory is presented in order to compensate for incomplete or missing data on market characteristics. Vertical cooperative advertising is an essential element of partnerships between manufacturers and retailers, allowing manufacturers to financially support their retailers' advertising efforts so as to increase sales for the entire supply chain. Given that such programs not only make up a considerable part of many companies' advertising budgets, but are also a controversial subject in many business relations, their correct design is of particular importance.

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.

Organizations are information intensive systems, operating in dynamic and competitive markets, structured around complex physical and political infrastructures. This book characterises the critical nature of these environments through strategies for business information technology management (BITM).

One of the most important tasks faced by decision-makers in business and government is that of selection. Selection problems are challenging in that they require the balancing of multiple, often conflicting, criteria. In recent years, a number of interesting decision aids have become available to assist in such decisions.
The aim of this book is to provide a comparative survey of many of the decision aids currently available. The first chapters present general ideas which underpin the methodologies used to design these aids. Subsequent chapters then focus on specific decision aids and demonstrate some of the software which implement these ideas. A final chapter provides a comparative analysis of their strengths and weaknesses.

Operations Research (OR) emerged in an effort to improve the effectiveness of newly inducted weapons and equipment during World War II. While rapid growth ofOR led to its becoming an important aid to decision making in all sectors including defense, its contribution in defense remained largely confined to classified reports. Very few books dealing with applications of quantitative decision making techniques in military have been published presumably due to limited availability ofrelevant information. The situation changed rapidly during the last few years. The recognition of the subject of Military Operations Research (MOR) gave tremendous boost to its development. Books and journals on MOR started appearing. The number of sessions on MOR at national and international conferences also registered an increase. The volume of teaching, training and research activities in the field of MOR at military schools and non-military schools enhanced considerably. Military executives and commanders started taking increasing interest in getting scientific answers to questions pertaining to weapon acquisition, threat perception and quantification, assessment of damage or casualties, evaluation of chance of winning a battle, force mix, deployment and targeting of weapons against enemy targets, war games and scenario evaluation. Most of these problems were being tackled on the basis of intuition, judgment and experience or analysis under very simple assumptions. In an increasingly sophisticated and complex defense scenario resulting in advances in equipment and communications, the need for supplementing these practices by scientific research in MOR became imperative.

Why do some corporate superstars collapse dramatically, while others survive and prosper over many decades? Is the fall primarily caused by 'technical factors', such as poor products and pricing, financial management or market choices, by self-aggrandisement, or perhaps by poor leadership attributes and capabilities? Greg Park argues that ultimately organisational survival and optimal performance over the long term is dependent upon collaborative wisdom. Within the dominant coalition of a successful community or corporation there is an inherited, pervasive, commonly and collectively held dominant logic, comprising leadership principles, perspectives and priorities, based upon universal values which are understood and accepted as satisfying the requirements and aspirations of each stakeholder. This collaborative wisdom ensures cohesive and consistent behaviour across and within every function of a complex, fast-moving organization. Its practical application is reflected in the daily operational decisions of leaders within the organisation, be they divisional, departmental heads or supervisors. Without collaborative wisdom organisational collapse is the inevitable result, primarily through the disintegration of belief, confidence, motivation, cohesion, advocacy and energy within and between key stakeholder groups. Collaborative Wisdom examines the nature and criticality of wisdom as a leadership attribute, how effective operational leadership is not just about knowledge and experience, but more fundamentally about a cognitive mental process which considers and consistently applies fundamental values, principles, perspectives and priorities in an analytical and affective manner. This ensures effective operational leadership and optimal organisational performance over the long term, informed by experience, instinct, intuition, but also by insight, judgment and ultimately, wisdom.

The scope of this book is limited to heuristics, metaheuristics, and approximate methods and algorithms as applied to planning and scheduling problems. While it is not possible to give a comprehensive treatment of this topic in one book, the aim of this work is to provide the reader with a diverse set of planning and scheduling problems and different heuristic approaches to solve them. The problems range from traditional single stage and parallel machine problems to more modern settings such as robotic cells and flexible job shop networks. Furthermore, some chapters deal with deterministic problems while some others treat stochastic versions of the problems. Unlike most of the literature that deals with planning and scheduling problems in the manufacturing and production environments, in this book the environments were extended to nontraditional applications such as spatial scheduling (optimizing space over time), runway scheduling, and surgical scheduling. The solution methods used in the different chapters of the book also spread from well-established heuristics and metaheuristics such as Genetic Algorithms and Ant Colony Optimization to more recent ones such as Meta-RaPS.