This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC's and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors' SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. ... The presentation includes geometric interpretation, linear programming duality, and the simplex method in its primal and dual forms. ... The authors have made an effort to collect ... the most useful recent ideas and algorithms in this area. ... A guide to the existing software is included as well." (Darinka Dentcheva, Mathematical Reviews, Issue 2006 c) "This is a graduate text in optimisation whose main emphasis is in stochastic programming. The book is clearly written. ... This is a good book for providing mathematicians, economists and engineers with an almost complete start up information for working in the field. I heartily welcome its publication. ... It is evident that this book will constitute an obligatory reference source for the specialists of the field." (Carlos Narciso Bouza Herrera, Zentralblatt MATH, Vol. 1104 (6), 2007)

This book highlights the use of an outcome-oriented view of performance to frame and assess the desirability of the effects produced by adopted policies, so to allow governments not only to consider effects in the short, but also the long run. Furthermore, it does not only focus on policy from the perspective of a single unit or institution, but also under an inter-institutional viewpoint. This book features theoretical and empirical research on how public organizations have evolved their performance management systems toward outcome measures that may allow one to better deal with wicked problems. Today, 'wicked problems' characterize most of governmental planning involving social issues. These are complex policy problems, underlying high risk and uncertainty, and a high interdependency among variables affecting them. Such problems cannot be clustered within the boundaries of a single organization, or referred to specific administrative levels or ministries. They are characterized by dynamic complexity, involving multi-level, multi-actor and multi-sectoral challenges. In the last decade, a number of countries have started to develop new approaches that may enable to improve cohesion, to effectively deal with wicked problems. The chapters in this book showcase these approaches, which encourage the adoption of more flexible and pervasive governmental systems to overcome such complex problems. Outcome-Based Performance Management in the Public Sector is divided into five parts. Part 1 aims at shedding light on problems and issues implied in the design and implementation of "outcome-based" performance management systems in the public sector. Then Part 2 illustrates the experiences, problems, and evolving trends in three different countries (Scotland, USA, and Italy) towards the adoption of outcome-based performance management systems in the public sector. Such analyses are conducted at both the national and local government levels. The third part of the book frames how outcome-based performance management can enhance public governance and inter-institutional coordination. Part 4 deals with the illustration of challenges and results from different public sector domains. Finally the book concludes in Part 5 as it examines innovative methods and tools that may support decision makers in dealing with the challenges of outcome-based performance management in the public sector. Though the book is specifically focused on a research target, it will also be useful to practitioners and master students in public administration .

Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.

Organizations are complex entities that must adapt the practices of their employees and management to meet the demands of a dynamic environment. Organizations are behavioral systems that coordinate interactions among its members and environment. Changing practices in one area of an organization can generate a reaction throughout the entire system, thus affecting the behaviors of those working within other areas, the experience of customers, and important organizational results. Behavioral Systems Analysis (BSA) focuses on these complex contingencies from the macro system all the way down to individual behavior. This book contains articles by internationally recognized experts in Behavioral Systems Analysis who discuss the role of organizational practices in their study of performance improvement and cultural change from both practical and conceptual perspectives. Business and non-profit managers will find tools and case studies to help understand and diagnose their organization's dynamics. Scholars will appreciate articles' theory and real-world descriptions when considering their own research direction. Finally, all students of management theory, behavior analysis, and human resources will find this collection a thought-provoking tool for their understanding of behavioral systems and their application in organizations. This book was published as a special issue in the Journal of Organizational Behavior Management.

Mention the phrase "bottom line," and the immediate thought tends to focus on a company's financial performance. Think again! There's an equally important factor that carries tremendous impact on that final total: operational performance measures.
Implementation of a performance improvement program can significantly improve a company's bottom line. Operational Performance Measurement: Increasing Total Productivity shows the way-featuring a new integrated theory of performance measurement, with a never-before-published measurement model that's applicable to any business activity.
Practical procedures and guidelines directly identify the variables that should be measured; guidelines to develop measurement systems; and how to analyze, interpret, and use performance methods effectively. Numerous diagrams, tables and examples make the principles and procedures easy to understand and implement.
While this performance measurement approach is simplicity itself, be prepared for powerful results!
Managers can put the theory into action right away- giving them better control, improved performance, increased personal productivity-and an easier day at work!
Operations, finance, administration and quality managers alike will find there's so much to gain when they're Operational Performance Measurement: Increasing Total Productivity ... and a better bottom line is just the beginning!

Accessible and easy to read guide in the best-selling Basics series The ideal guide for beginners or non-specialists who need to grasp the fundamentals of management User-friendly approach, including features such as key terms for each chapter, chapter summaries and annotated suggestions for further reading Draws on many examples from around the world including North America (such as Enron, Coca Cola and General Motors) Interdisciplinary appeal - will also sell to the Leisure & Tourism market, Arts Management and Media Management markets New edition includes the topics of globalisation, CSR, entrepreneurship, sustainability, risk, resilience and disaster management

Why do carefully planned projects fail? Projects are affected, for good or ill, by the humans who undertake them. If the plan fails to take account of the psychology of managing people and the psychology of managing change there may be trouble ahead. Sharon De Mascia's Project Psychology uses human behaviour and emerging psychological models to provide an insight into the successful management of people in projects. By selecting the right team, facilitating a common vision and by gaining a psychological understanding of how the team and the project stakeholders interact together, a project manager improves the chance of a successful outcome. Whether you are looking to set up and manage a new project or working to develop the competence and maturity of your organization's project management capability, Project Psychology will provide you with insights and tools for making sense of the people involved and for managing them to best effect.

The 21st century promises to be an era dominated by international response to c- tain global environmental challenges such as climate change, depleting biodiversity and biocapacity as well as general atmospheric, water and soil pollution problems. Consequently, Environmental decision making (EDM) is a socially important ?eld of development for Operations Research and Management Science (OR/MS). - certainty is an important feature of these decision problems and it intervenes at very different time and space scales. The Handbook on "Uncertainty and Environmental Decision Making" provides a guided tour of selected methods and tools that OR/MS offer to deal with these issues. Below, we brie?y introduce, peer reviewed, chapters of this handbook and the topics that are treated by the invited authors. The ?rst chapter is a general introduction to the challenges of environmental decision making, the use of OR/MS techniques and a range of tools that are used to deal with uncertainty in this domain.

This book identifies the responsibilities of management in the regulatory territories of the FAA (USA), the EASA (European Union) and the GCAA (UAE), identifying the daily challenges of leadership in ensuring their company is meeting the regulatory obligations of compliance, safety and security that will satisfy the regulator while also meeting the fiducial responsibilities of running an economically viable and efficient lean company that will satisfy the shareholders.

Detailing each responsibility of the Accountable Manager, the author breaks them down to understandable and achievable elements where methods, systems and techniques can be applied to ensure the role holder is knowledgeable of accountabilities and is confident that they are not only compliant with the civil aviation regulations but also running an efficient and effective operation. This includes the defining of an Accountable Manager "tool kit" as well as possible software "dashboards" that focus the Accountable Manager on the important analytics, such as the information and data available, as well as making the maximum use of their expert post holder team.

This book will be of interest to leadership of all aviation- related companies, such as airlines, charter operators, private and executive operators, flying schools, aircraft and component maintenance facilities, aircraft manufacturers, engine manufacturers, component manufacturers, regulators, legal companies, leasing companies, banks and finance houses, departments of transport, etc; any relevant organisation regulated and licensed by civil aviation authority. It can also be used by students within a wide range of aviation courses at colleges, universities and training academies.

Multicriteria analysis is a rapidly growing aspect of operations research and management science, with numerous practical applications in a wide range of fields. This book presents all the recent advances in multicriteria analysis, including multicriteria optimization, goal programming, outranking methods, and disaggregation techniques. The latest developments on robustness analysis, preference elicitation, and decision making when faced with incomplete information, are also discussed, together with applications in business performance evaluation, finance, and marketing. Finally, the interactions of multicriteria analysis with other disciplines are also explored, including among others data mining, artificial intelligence, and evolutionary methods.

Games, or contexts of strategic interaction, pervade and suffuse our lives and the lives of all organisms. How are we to make sense of and cope with such situations? How should an agent play? When will and when won't cooperation arise and be maintained? Using examples and a careful digestion of the literature, Agents, Games, and Evolution: Strategies at Work and Play addresses these encompassing themes throughout, and is organized into four parts: Part I introduces classical game theory and strategy selection. It compares ideally rational and the "naturalist" approach used by this book, which focuses on how actual agents chose their strategies, and the effects of these strategies on model systems. Part II explores a number of basic games, using models in which agents have fixed strategies. This section draws heavily on the substantial literature associated with the relevant application areas in the social sciences. Part III reviews core results and applications of agent-based models in which strategic interaction is present and for which design issues have genuine practical import. This section draws heavily on the substantial literature associated with the application area to hand. Part IV addresses miscellaneous topics in strategic interaction, including lying in negotiations, reasoning by backward induction, and evolutionary models. Modeled after the authors' Agents, Games, and Evolution course at the University of Pennsylvania, this book keeps mathematics to a minimum, focusing on computational strategies and useful methods for dealing with a variety of situations.

This book highlights recent advances in the field of districting, territory design, and zone design. Districting problems deal essentially with tactical decisions, and involve mainly dividing a set of geographic units into clusters or territories subject to some planning requirements. This book presents models, theory, algorithms (exact or heuristic), and applications that would bring research on districting systems up-to-date and define the state-of-the-art. Although papers have addressed real-world problems that require districting or territory division decisions, this is the first comprehensive book that directly addresses these problems. The chapters capture the diverse nature of districting applications, as the book is divided into three different areas of research. Part I covers recent up-to-date surveys on important areas of districting such as police districting, health care districting, and districting algorithms based on computational geometry. Part II focuses on recent advances on theory, modeling, and algorithms including mathematical programming and heuristic approaches, and finally, Part III contains successful applications in real-world districting cases.

The Cloud Computing and Services Science book comprises a collection of the best papers presented at the International Conference on Cloud Computing and Services Science (CLOSER), which was held in The Netherlands in May 2011. In netting papers from the conference researchers and experts from all over the world explore a wide-ranging variety of the emerging Cloud Computing platforms, models, applications and enabling technologies. Further, in several papers the authors exemplify essential links to Services Science as service development abstraction, service innovation, and service engineering, acknowledging the service-orientation in most current IT-driven structures in the Cloud.

The Cloud Computing and Services Science book is organized around important dimensions of technology trends in the domain of cloud computing in relation to a broad scientific understanding of modern services emerging from services science. The papers of this book are inspired by scholarly and practical work on the latest advances related to cloud infrastructure, operations, security, services, and management through the global network. This book includes several features that will be helpful, interesting, and inspirational to students, researchers as well as practitioners. Professionals and decision makers working in this field will also benefit from this book

This book offers the first comprehensive and critical literature review of fuzzy pairwise comparison methods derived from methods originally developed for crisp pairwise comparison matrices. It proposes new fuzzy extensions of these methods and provides a detailed study of the differences and analogies between all the reviewed methods, as well as a detailed description of their drawbacks, with the help of many numerical examples. In order to prevent the drawbacks related to the reviewed fuzzy pairwise comparison methods, the book introduces constrained fuzzy arithmetic in fuzzy extension of the pairwise comparison methods. It proposes new fuzzy pairwise comparison methods based on constrained fuzzy arithmetic and critically compares them with the reviewed methods. It describes the application of the newly developed methods to incomplete large-dimensional pairwise comparison matrices showcased in a real-life case study. Written for researchers, graduate and PhD students interested in multi-criteria decision making methods based on both crisp and fuzzy pairwise comparison matrices, this self-contained book offers an overview of cutting-edge research and all necessary information to understand the described tools and use them in real-world applications.

This book is an undergraduate text that introduces students to commonly used statistical methods in economics. Using examples based on contemporary economic issues and readily available data, it not only explains the mechanics of the various methods, but also guides students to connect statistical results to detailed economic interpretations. Because the goal is for students to be able to apply the statistical methods presented, online sources for economic data and directions for performing each task in Excel are also included.

The book includes the latest research advances and cutting-edge analyses of real case studies in the disciplines of Industrial Engineering and Operations Management from diverse international contexts. This work presents a revised version of the best papers presented at the XIII International Conference on Industrial Engineering and Industrial Management promoted by ADINGOR (Asociacion para el Desarrollo de la Ingenieria de Organizacion), which took place at the Polytechnic School of Engineering of Gijon (University of Oviedo), Asturias, Spain, from July 11th to 12th, 2019.

Written by international contributors, Learning Curves: Theory, Models, and Applications first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve.

Traditionally, books on learning curves have focused either on cost accounting or production planning and control. In these books, the learning curve has been treated as a forecasting tool. This book synthesizes current research and presents a clear picture of organizational learning curves. It explores how organizations improve other measures of organizational performance including quality, inventory, and productivity, then looks inside the learning curve to determine the actual processes through which organizations learn.

Defines the correct cost optimization process Provides detailed explanation of cost estimating techniques Presents cost estimating techniques for various manufacturing processes Offers cost based negotiation training Explains how to build a cost engineering organization

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This "big data" provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

This book Algebraic Modeling Systems - Modeling and Solving Real World Optimization Problems - deals with the aspects of modeling and solving real-world optimization problems in a unique combination. It treats systematically the major algebraic modeling languages (AMLs) and modeling systems (AMLs) used to solve mathematical optimization problems. AMLs helped significantly to increase the usage of mathematical optimization in industry. Therefore it is logical consequence that the GOR (Gesellschaft fur Operations Research) Working Group Mathematical Optimization in Real Life had a second meeting devoted to AMLs, which, after 7 years, followed the original 71st Meeting of the GOR (Gesellschaft fur Operations Research) Working Group Mathematical Optimization in Real Life which was held under the title Modeling Languages in Mathematical Optimization during April 23-25, 2003 in the German Physics Society Conference Building in Bad Honnef, Germany. While the first meeting resulted in the book Modeling Languages in Mathematical Optimization, this book is an offspring of the 86th Meeting of the GOR working group which was again held in Bad Honnef under the title Modeling Languages in Mathematical Optimization.

Over the last three decades the world economy has grown strongly on the back of 'globalization' supported by the policies of free-trade, open markets and privatisation. Support has also grown for the concept of 'sustainability', meeting the needs of the present without compromising the ability of future generations to meet their own needs. But as the Earth's systems come under increasing strain, the inherent conflict between sustainability and globalization has been exposed. Green Outcomes in a Real World examines the shift in thinking required to reconcile these two important areas of policy. In this ground breaking book, Peter McManners has coined the term 'Proximization' to define a new policy framework. The principles of Proximization are: 'sustainability', 'subsidiarity', 'primacy of the state' and 'market economics' and the application of these familiar concepts towards a sustainable globalised world is novel and different. The author argues that adherence to the principles of proximization will return world society to a stable natural order, and will mean changes. Global commodity flows will reduce and barriers to migration will increase. National governments will demand more control over their finances leading to restrictions on capital flows. Indeed, Peter believes that an element of 'selfish determination' is needed. The new world order will be sustainable by design. Global organisations such as the UN, national governments and global corporations will have to understand and apply a different paradigm. The arguments in this book do not reflect the idealism or even naivety of some of the green movement. This book is about hard-edged reality presented by an author with huge experience and a deep understanding of the business perspective. It will appeal to a wide range of professionals involved in setting policy and future direction for businesses, governments, and non-governmental bodies, as well as to those with an academic interest in business, economics, social and environmental issues, and public policy.

This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, provides an overview of selection constructive, selection perturbative, generation constructive and generation perturbative hyper-heuristics, and then a formal definition of hyper-heuristics. The chapters in the second part of the book examine applications of hyper-heuristics in vehicle routing, nurse rostering, packing and examination timetabling. The third part of the book presents advanced topics and then a summary of the field and future research directions. Finally the appendices offer details of the HyFlex framework and the EvoHyp toolkit, and then the definition, problem model and constraints for the most tested combinatorial optimization problems. The book will be of value to graduate students, researchers, and practitioners.

Higher Education Consumer Choice provides a comprehensive and highly focused critical analysis of research on HE consumer choice behaviour in the UK and around the world. Ideal for students, scholars and marketing practitioners interested in consumer choice and behaviour in higher education markets, the book explores the background and context to research on HE choice including globalization, changing supply and demand, fees and costs, and concerns about social disadvantage. Focusing on personal factors that influence consumer choice, group aspects of consumer behaviour such as cultural and ethnic differences, as well as theoretical and research models, this book is designed to stimulate new debate and criticism of HE consumer choice.

Spatial planning is about dealing with our 'everyday' environment. In A Planner's Encounter with Complexity we present various understandings of complexity and how the environment is considered accordingly. One of these considerations is the environment as subject to processes of continuous change, being either progressive or destructive, evolving non-linearly and alternating between stable and dynamic periods. If the environment that is subject to change is adaptive, self-organizing, robust and flexible in relation to this change, a process of evolution and co-evolution can be expected. This understanding of an evolving environment is not mainstream to every planner. However, in A Planner's Encounter with Complexity, we argue that environments confronted with discontinuous, non-linear evolving processes might be more real than the idea that an environment is simply a planner's creation. Above all, we argue that recognizing the 'complexity' of our environment offers an entirely new perspective on our world and our environment, on planning theory and practice, and on the raison d'Atre of the planners that we are. A Planner's Encounter with Complexity is organized into 17 chapters. It begins with the interplay of planning and complexity from the perspective of contemporary planning theory. It continues by critically assessing planning theory and practice in the light of the interdisciplinary debate regarding complexity thinking. As the book progresses, it positions itself ever closer to the perspective of complexity thinking, looking at the planning discipline 'from the outside in', clarifying the facets of complexity and its importance in planning. Finally, conceptual and theoretical developments towards more applied examples are identified in order to see the interplay of planning and complexity in practice. This book emphasizes the importance of complexity in planning, clarifies many of the concepts and theories, presents examples on planning and complexity, and proposes new ideas and methods for planning.

Scilab and its Scicos block diagram graphical editor, with a special emphasis on modeling and simulation tools. The first part is a detailed Scilab tutorial, and the second is dedicated to modeling and simulation of dynamical systems in Scicos. The concepts are illustrated through numerous examples, and all code used in the book is available to the reader.