Operations Research is a field whose major contribution has been to propose a rigorous fonnulation of often ill-defmed problems pertaining to the organization or the design of large scale systems, such as resource allocation problems, scheduling and the like. While this effort did help a lot in understanding the nature of these problems, the mathematical models have proved only partially satisfactory due to the difficulty in gathering precise data, and in formulating objective functions that reflect the multi-faceted notion of optimal solution according to human experts. In this respect linear programming is a typical example of impressive achievement of Operations Research, that in its detenninistic fonn is not always adapted to real world decision-making : everything must be expressed in tenns of linear constraints ; yet the coefficients that appear in these constraints may not be so well-defined, either because their value depends upon other parameters (not accounted for in the model) or because they cannot be precisely assessed, and only qualitative estimates of these coefficients are available. Similarly the best solution to a linear programming problem may be more a matter of compromise between various criteria rather than just minimizing or maximizing a linear objective function. Lastly the constraints, expressed by equalities or inequalities between linear expressions, are often softer in reality that what their mathematical expression might let us believe, and infeasibility as detected by the linear programming techniques can often been coped with by making trade-offs with the real world.

This book examines sustainable wealth formation and dynamic decision-making. The global economy experienced a veritable meltdown of asset markets in the years 2007-9, where many funds were overexposed to risky returns and suffered considerable losses. On the other hand, the long-term upswing in the stock market since 2010 has led to asset price booms and some new, but also uneven, wealth formation. In this book a broader set of constraints and guidelines for asset management and wealth accumulation is developed. The authors investigate how wealth formation and the proper management of financial funds can help to adequately buffer income risk and obtain sufficient risk-free income at a later stage of life, while also being socially and environmentally sustainable. The book explores behavioral and institutional rules for decision-making that reflect such constraints and guidelines, without necessarily being optimal in the narrow sense. The authors explain the need for such a dynamic decision-making and dynamic re-balancing of portfolios, by putting forward dynamic programming as an approach to dynamic decision-making that can allow sustainable wealth accumulation and dynamic asset allocation to be successfully integrated. This book provides a clear and comprehensive treatment of asset accumulation and dynamic portfolio models with an emphasis on long term and sustainable wealth formation. An important concern in public debate is the sustainability of our economy and this book employs cutting edge quantitative techniques and models to highlight important facts that cannot be disputed under any reasonable assumptions. It has the potential to become a standard reference for both academic researchers and quantitatively trained practitioners. Eckhard Platen, Professor of Quantitative Finance, University of Technology Sydney, Australia This book should be read by both academics and practitioners alike. The former will find intellectually rigorous discussions and innovative solutions. The latter may find a few of the concepts a bit challenging. Yet, theory and technology are there to help simplify the work of those who worry about what time it is rather than how to make a watch--- but they do need a watch. Jean Brunel, Founder of Brunel Associates and Editor of The Journal of Wealth Management

This volume describes how frontier efficiency methodologies such as Data Envelopment Analysis (DEA) and other techniques such as multi-criteria decision makingcan help service industries to improve their performance by providing a ranking of best-practice efficient service units and by identifying sources of inefficiency for each service unit. It explains how they can be used to determine potential improvement targets for each of the inefficient service units, to identify peers for each service organization and to provide a basis for continuous performance improvement. Presenting applications in a variety of industries, this book will be useful for the service management to improve service productivity, profitability, sustainability and quality and effectiveness of service deliveries. A free trial version of the World s leading Data Envelopment Analysis Software (PIM-DEA) is available for readers of this book. "

The Economic Order Quantity (EOQ) inventory model first appeared in 1913, and in its centennial, it is still one of the most important inventory models. Despite the abundance of both classical and new research results, there was (until now) no comprehensive reference source that provides the state-of-the-art findings on both theoretical and applied research on the EOQ and its related models. This edited handbook puts together all these interesting works and the respective insights into an edited volume.

The handbook contains papers which explore both the deterministic and the stochastic EOQ-model based problems and applications. It is organized into three parts: Part I presents three papers that provide an introduction and review of the EOQ, a consideration of multi-period lot sizing with stationary demand, and EOQ models with supply disruptions. Part II includes four technical analyses on single-echelon EOQ- model based inventory problems. Part III consists of five papers on applications of the EOQ model for multi-echelon supply chain inventory analysis."

Industries rely more and more on advanced technology. Accelerated computer evolution makes large-scale computation practical. Many enterprises are be ginning to benefit from more efficient allocation of resources and more effective planning, scheduling, manufacturing, and distribution by adopting state-of-the art decision support systems. Academics increasingly emphasize application driven research. All these forces have moved optimization from a pure class room and textbook terminology to an accepted tool in today's business world. This book chronicles and describes applications of combinatorial optimization in industry. A wide range of applications is included: manpower planning * production planning * job sequencing and scheduling * manufacturing layout design * facility planning * vehicle scheduling and routing * retail seasonal planning * I! space shuttle scheduling, and telecommunication network design . * The applications covered in this book comprise a representative set of industry sectors including electronics, airlines, manufacturing, tobacco, retail, telecom munication, defense, and livestock. These examples should encourage opera tions researchers and applied mathematicians by pointing out how the impor tance and practicality of optimization is starting to be realized by the manage ment of various organizations and how some pioneering developments in this field are beginning to bear fruit.

This book describes the inferential and modeling advantages that this distribution, together with its generalizations and modifications, offers. The exposition systematically unfolds with many examples, tables, illustrations, and exercises. A comprehensive index and extensive bibliography also make this book an ideal text for a senior undergraduate and graduate seminar on statistical distributions, or for a short half-term academic course in statistics, applied probability, and finance.

When I wrote the book Quantitative Sociodynamics, it was an early attempt to make methods from statistical physics and complex systems theory fruitful for the modeling and understanding of social phenomena. Unfortunately, the ?rst edition appeared at a quite prohibitive price. This was one reason to make these chapters available again by a new edition. The other reason is that, in the meantime, many of the methods discussed in this book are more and more used in a variety of different ?elds. Among the ideas worked out in this book are: 1 * a statistical theory of binary social interactions, * a mathematical formulation of social ?eld theory, which is the basis of social 2 force models, * a microscopic foundation of evolutionary game theory, based on what is known today as 'proportional imitation rule', a stochastic treatment of interactions in evolutionary game theory, and a model for the self-organization of behavioral 3 conventions in a coordination game. It, therefore, appeared reasonable to make this book available again, but at a more affordable price. To keep its original character, the translation of this book, which 1 D. Helbing, Interrelations between stochastic equations for systems with pair interactions. Ph- icaA 181, 29-52 (1992); D. Helbing, Boltzmann-like and Boltzmann-Fokker-Planck equations as a foundation of behavioral models. PhysicaA 196, 546-573 (1993). 2 D. Helbing, Boltzmann-like and Boltzmann-Fokker-Planck equations as a foundation of beh- ioral models. PhysicaA 196, 546-573 (1993); D.

"Decision Systems and Non-stochastic Randomness" is the first systematic presentation and mathematical formalization (including existence theorems) of the statistical regularities of non-stochastic randomness. The results presented in this book extend the capabilities of probability theory by providing mathematical techniques that allow for the description of uncertain events that do not fit standard stochastic models. The book demonstrates how non-stochastic regularities can be incorporated into decision theory and information theory, offering an alternative to the subjective probability approach to uncertainty and the unified approach to the measurement of information. This book is intended for statisticians, mathematicians, engineers, economists or other researchers interested in non-stochastic modeling and decision theory.

The financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain. Decision Policies for Production Networks presents recent convergent research on developing policies for operating production networks including details of practical control and decision techniques which can be applied to improve the effectiveness and economic efficiency of production networks worldwide. Researchers and practitioners come together to explore a wide variety of approaches to a range of topics including:

WIP and equipment management policies,

Material release policies,

Machine, factory, and supply chain network policies for delivery in the face of supply and demand variability, and

Conflicts between complex production network models and their controlling policies.

Case studies and relevant mathematical techniques are included to support and explain techniques such as heuristics, global and hierarchical optimization, control theory and filtering approaches related to complex systems or traffic flows. Decision Policies for Production Networks acts as handbook for researchers and practitioners alike, providing findings and information which can be applied to develop methods and advance further research across production networks.
"

Organizations - whether profit or nonprofit, services or manufacturing - need to be able to adapt and transform their cultures to succeed. Yet cultural transformation can seem either too easy or completely overwhelming. "Transforming Culture" shows how effective and sustainable cultural transformation can be achieved even in a challenging environment such as a General Motors manufacturing plant. The authors offer both a practical approach and tools to draw on the energy and ideas of employees and executives, remove obstacles to change, and create durable improvements.

A Perspective on Two Decades of Rapid Modeling It is an honor for me to be asked to write a foreword to the Proceedings of the 1st Rapid Modeling Conference. In 1987, when I coined the term "Rapid Modeling" to denote queuing modeling of manufacturing systems, I never imagined that two decades later there would be an international conference devoted to this topic I am delighted to see that there will be around 40 presentations at the conference by leading researchers from aroundthe world, and about half of these presentationsare represented by written papers published in this book. I congratulate the conference organizers and program committee on the success of their efforts to hold the ?rst ever conference on Rapid Modeling. Attendees at this conferencemight?nd it interesting to learn about the history of the term Rapid Modeling in the context it is used here. During the fall of 1986 I was invited to a meeting at the Headquarters of the Society of Manufacturing Engineers (SME) in Dearborn, Michigan. By that time I had successfully demonstrated s- eral industry applications of queuing network models at leading manufacturers in the USA. Although in principle the use of queuing networks to model manufact- ing systems was well known in the OR/MS community and many papers had been published, the actual use of suchmodelsby manufacturingprofessionalswas almost nonexistent.

Internet is starting to permeate politics much as it has previously revolutionised education, business or the arts. Thus, there is a growing interest in areas of e-government and, more recently, e-democracy. However, most attempts in this field have just envisioned standard political approaches facilitated by technology, like e-voting or e-debating. Alternatively, we could devise a more transforming strategy based on deploying web based group decision support tools and promote their use for public policy decision making.

This book delineates how this approach could be implemented. It addresses foundations, basic methodologies, potential implementation and applications, together with a thorough discussion of the many challenging issues.

This innovative text will be of interest to students, researchers and practitioners in the fields of e-government, e-democracy and e-participation and research in decision analysis, negotiation analysis and group decision support.

Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.

The past two decades have seen a great deal of research into the stochastic modelling of production, manufacturing, and inventory systems for the purpose of improving their performance. This book provides a graduate-level introduction to these techniques covering exact, approximate, and numerical techniques. The author has aimed to strike a balance between theoretical issues and the practical aspects of modelling manufacturing systems. It is based on graduate courses given to operations research and industrial engineering students and includes numerous examples and exercises.

This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail. The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.

Decision Criteria and Optimal Inventory Processes provides a theoretical and practical introduction to decision criteria and inventory processes. Inventory theory is presented by focusing on the analysis and processes underlying decision criteria. Included are many state-of-the-art criterion models as background material. These models are extended to the authors' newly developed fuzzy criterion models which constitute a general framework for the study of stochastic inventory models with special focus on the real world inventory theoretic reservoir operations problems. The applications of fuzzy criterion dynamic programming models are illustrated by reservoir operations including the integrated network of reservoir operation and the open inventory network problems. An interesting feature of this book is the special attention it pays to the analysis of some theoretical and applied aspects of fuzzy criteria and dynamic fuzzy criterion models, thus opening up a new way of injecting the much-needed type of non-cost, intuitive, and easy-to-use methods into multi-stage inventory processes. This is accomplished by constructing and optimizing the fuzzy criterion models developed for inventory processes. Practitioners in operations research, management science, and engineering will find numerous new ideas and strategies for modeling real world multi- stage inventory problems, and researchers and applied mathematicians will find this work a stimulating and useful reference.

Regardless of where we live, the management of the public sector impacts on our lives. Hence, we all have an interest, one way or another, in the achievement of efficiency and productivity improvements in the activities of the public sector. For a government agency that provides a public service, striving for unreasonable benchmark targets for efficiency may lead to a deterioration of service quality, along with an increase in stress and job dissatisfaction for public sector employees. Slack performance targets may lead to gross inefficiency, poor quality of service, and low self-esteem for employees. In the case of regulation, inappropriate policies can lead to unprecedented disasters. Examples include the decimation of fish stocks through mismanagement of fisheries, and power blackouts through inappropriate restrictions on electricity generators and distributors. Efficient taxation policies minimise the tax bill for citizens. In all of these cases, efficient management is required, although it is often unclear how to assess this efficiency. In this volume, several authors consider various aspects and contexts of performance measurement. Hence, this volume represents a unique collection of advances in efficiency assessment for the public sector by leading researchers in the field. Efficiency in the Public Sector is divided into two sections. The first is titled "Issues in Public Sector Efficiency Evaluation" and comprises of chapters 1-4. The second section is titled "Efficiency Analysis in the Public Sector - Advances in Theory and Practice." This division is somewhat arbitrary, in the sense there are significant overlapping themes in both sections. However, it serves to separate chapters that can be characterised as dealing with broader issues (Section I), from chapters that can be characterised as focusing on specific theoretical problems and empirical cases (Section II).

The problem of allocating scarce resources over time to perform a given set of activities - that is, project scheduling - appears in the vast spectrum of real-world situations. Over the last forty years project scheduling problems have been carefully studied, resulting in a considerable body of knowledge. Recently, however, the power and ubiquity of the computer has had a pronounced effect on research in project scheduling and project scheduling models. As a result, considerable progress has been made in all directions of modeling and finding solutions to these problems. This volume is a state-of-the-art treatment of Project Scheduling in general and of recent developments in particular. Part I deals with classical models. By classical model' we mean the deterministic problems involving discrete resources only and the evaluation of schedules on the basis of a single criterion. This term covers a wide variety of problems, including (discrete) resource-duration interaction, i.e. multi-mode models. Part 2 deals with heuristic algorithms for these models. It is complemented by chapters treating such important problems as benchmark instances, interval capacity consistency tests, and the evolution of software quality for (classical) project scheduling problems. In Part 3 the most important new or non-classical' models are considered. These include probabilistic and fuzzy models, and continuous resources as well as multi-criteria formulations and knowledge-based systems. Part 4 contains some important extensions and/or applications of the project scheduling problems considered in the previous chapters.

Agent-based modeling and social simulation have emerged as both developments of and challenges to the social sciences. The developments include agent-based computational economics and investigations of theoretical sociological concepts using formal simulation techniques. Among the challenges are the development of qualitative modeling techniques, implementation of agent-based models to investigate phenomena for which conventional economic, social, and organizational models have no face validity, and the application of physical modeling techniques to social processes. Bringing together diverse approaches to social simulation and research agendas, this book presents a unique collection of contributions from the First World Congress on Social Simulation, held in 2006 in Kyoto, Japan. The work emerged from the collaboration of the Pacific Asian Association for Agent-Based Approach in Social Systems Sciences, the North American Association for Computational Social and Organizational Science, and the European Social Simulation Association.

Advances in Business and Management Forecasting is a blind refereed serial publication published on an annual basis. The objective of this research annual is to present state-of-the-art studies in the application of forecasting methodologies to such areas as sales, marketing, and strategic decision making. (An accurate, robust forecast is critical to effective decision making.) It is the hope and direction of the research annual to become an applications and practitioner-oriented publication.
The topics will normally include sales and marketing, forecasting, new product forecasting, judgmentally-based forecasting, the application of surveys to forecasting, forecasting for strategic business decisions, improvements in forecasting accuracy, and sales response models. It is both the hope and direction of the editorial board to stimulate the interest of the practitioners of forecasting to methods and techniques that are relevant.
In Volume 5, there are sections devoted to financial applications of forecasting, as well as demand forecasting. There is, also, a section on general business applications of forecasting, as well as one on forecasting methodologies.
*Presents state-of-the-art studies in the application of forecasting methodologies to such areas as sales, marketing, and strategic decision making.
*Publishes annually

Hybrid Optimization focuses on the application of artificial intelligence and operations research techniques to constraint programming for solving combinatorial optimization problems. This book covers the most relevant topics investigated in the last ten years by leading experts in the field, and speculates about future directions for research.

This book includes contributions by experts from different but related areas of research including constraint programming, decision theory, operations research, SAT, artificial intelligence, as well as others. These diverse perspectives are actively combined and contrasted in order to evaluate their relative advantages.

This volume presents techniques for hybrid modeling, integrated solving strategies including global constraints, decomposition techniques, use of relaxations, and search strategies including tree search local search and metaheuristics. Various applications of the techniques presented as well as supplementary computational tools are also discussed.

The "EffizienzCluster LogistikRuhr" was a winner in the Leading Edge Science Cluster competition run by the German federal Ministry of Education and Research. The mission and aim of the "EffizienzCluster LogistikRuhr" is to facilitate tomorrow's individuality - in the sense of individual goods supply, mobility, and production - using 75 percent of today's resources. Efficiency - both in economical and ecological terms - is enabled by state-of-the-art and innovative logistical solutions including transportation, production and intralogistics. These proceedings "Efficiency and Logistics" give first answers from 27 research projects as an insight into the current state of research of Europe's leading research and development cluster in logistics and as a contribution to the discussion on how logistics as a science can help to cope with foreseeable resource shortage and sustainability as global challenges.

Previously, the conventional wisdom about organizations was "If it's not broken, then don't fix it. " Today, the new dictum seems to be "If it works, make it work better. " There is a shift from a posture of reaction to one that embraces change. The prevailing wisdom is changing because many of our organizations are now or will soon be in a state of crisis. Every day we read about a proud old firm going bankrupt, manufacturers who must cut costs and retrench in order to survive, and failures in our governmental agencies. Who's next? Many organizations are failing but others are doing well. All wonder if something terrible could happen to their organization. Thus, it seems prudent to anticipate and proactively manage change rather than to passively sit by until some crisis strikes. All of us know that any organization can be improved. There will always be a gap between some desired state and our current reality. There will always be differences among people about what is desirable and what is not. Every change energizes these gaps. Because there are so many changes taking place, it is no wonder that there is continuous clamor for organizational change. These gaps and differences are the source of problems. Once a problem is recognized and agreed to, efforts are made to generate a solution to it. Every solution has both its intended and unintended consequences.

This book arose out of an invited feature article on visualization and opti mization that appeared in the ORSA Journal on Computing in 1994. That article briefly surveyed the current state of the art in visualization as it ap plied to optimization. In writing the feature article, it became clear that there was much more to say. Apparently others agreed, and thus this book was born. The book is targeted primarily towards the optimization community rather than the visualization community. Although both optimization and visualization both seek to help people understand complex problems, prac titioners in one field are generally unaware of work in the other field. Given the common goals of the respective fields, it seemed fruitful to consider how each can contribute to the other. One might argue that this book should not be focused specifically on optimization but on decision making in general. Perhaps, but it seems that there is sufficient material to create a book targeted specifically to optimization. Certainly many of the ideas presented in the book are appli cable to other areas, including computer simulation, decision theory and stochastic modeling. Another book could discuss the use of visualization in these areas."

Studies in generalized convexity and generalized monotonicity have significantly increased during the last two decades. Researchers with very diverse backgrounds such as mathematical programming, optimization theory, convex analysis, nonlinear analysis, nonsmooth analysis, linear algebra, probability theory, variational inequalities, game theory, economic theory, engineering, management science, equilibrium analysis, for example are attracted to this fast growing field of study. Such enormous research activity is partially due to the discovery of a rich, elegant and deep theory which provides a basis for interesting existing and potential applications in different disciplines. The handbook offers an advanced and broad overview of the current state of the field. It contains fourteen chapters written by the leading experts on the respective subject; eight on generalized convexity and the remaining six on generalized monotonicity.