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Books > Business & Economics > Business & management > Management & management techniques > Operational research
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.
The Handbook of Mathematical Economics aims to provide a definitive source, reference, and teaching supplement for the field of mathematical economics. It surveys, as of the late 1970's the state of the art of mathematical economics. This is a constantly developing field and all authors were invited to review and to appraise the current status and recent developments in their presentations. In addition to its use as a reference, it is intended that this Handbook will assist researchers and students working in one branch of mathematical economics to become acquainted with other branches of this field. Volume I deals with Mathematical Methods in Economics, including reviews of the concepts and techniques that have been most useful for the mathematical development of economic theory. Volume II elaborates on Mathematical Approaches to Microeconomic Theory, including consumer, producer, oligopoly, and duality theory, as well as Mathematical Approaches to Competitive Equilibrium including such aspects of competitive equilibrium as existence, stability, uncertainty, the computation of equilibrium prices, and the core of an economy.
Data Envelopment Analysis (DEA) is often overlooked in empirical work such as diagnostic tests to determine whether the data conform with technology which, in turn, is important in identifying technical change, or finding which types of DEA models allow data transformations, including dealing with ordinal data.Advances in Data Envelopment Analysis focuses on both theoretical developments and their applications into the measurement of productive efficiency and productivity growth, such as its application to the modelling of time substitution, i.e. the problem of how to allocate resources over time, and estimating the 'value' of a Decision Making Unit (DMU).
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.
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 book systematically studies how game theory can be used to improve security in chemical industrial areas, capturing the intelligent interactions between security managers and potential adversaries. The recent unfortunate terrorist attacks on critical infrastructures show that adversaries are intelligent and strategic. Game theoretic models have been extensively used in some domains to model these strategic adversaries. However, there is a lack of such advanced models to be employed by chemical security managers. In this book, game theoretic models for protecting chemical plants as well as clusters are proposed. Different equilibrium concepts are explored, with user-friendly explanation of how to reflect them to realistic cases. Based on efficient analysis of the properties of security issues in chemical plants/clusters, models in this book are capable to support resources allocations, cost-effectiveness analysis, cooperation incentives and alike.
This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address riskneutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on integrated disruption mitigation and recovery decision-making and innovative, computationally efficient multi-portfolio approach to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on realworld supply chain disruption management problems, illustrate the material presented and provide managerial insights. Many propositions formulated in the book lead to a deep understanding of the properties of developed stochastic mixed integer programs and optimal solutions. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into six main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply and demand portfolios and production and inventory scheduling, Part V deals with selection of resilient supply portfolio in multitier supply chain networks; and Part VI addresses selection of cybersecurity safequards portfolio for disruption management of information flows in supply chains.
This handbook gathers state-of-the-art research on optimization problems in power distribution systems, covering classical problems as well as the challenges introduced by distributed power generation and smart grid resources. It also presents recent models, solution techniques and computational tools to solve planning problems for power distribution systems and explains how to apply them in distributed and variable energy generation resources. As such, the book therefore is a valuable tool to leverage the expansion and operation planning of electricity distribution networks.
The Handbook of Mathematical Economics aims to provide a definitive source, reference, and teaching supplement for the field of mathematical economics. It surveys, as of the late 1970's the state of the art of mathematical economics. This is a constantly developing field and all authors were invited to review and to appraise the current status and recent developments in their presentations. In addition to its use as a reference, it is intended that this Handbook will assist researchers and students working in one branch of mathematical economics to become acquainted with other branches of this field. Volume 1 deals with "Mathematical Methods in Economics," including reviews of the concepts and techniques that have been most useful for the mathematical development of economic theory. For more information on the Handbooks in Economics series,
please see our home page on http:
//www.elsevier.nl/locate/hes
This book introduces the fundamental principles of understanding business requirements to apply enterprise resource planning (ERP) in order to meet business needs. The book also helps readers understand the usage of ERP for monitoring and controlling business processes, while providing practical oriented solutions to the design and implementation of ERP. Using the provided framework, a business can decide to provide more value at lower cost which increases its competitive advantage. This should be an ideal reference for executives, researchers and consultants in project management of ERP. ERP can be considered to be an integrated package of business process. The scope of ERP determines the extent of automation of business process. For example if ERP covers Human Resource (HR) and finance business processes only, then business process related HR and finance are automated. Typically business process that are automated in HR and finance employee entry and exist process, allocation of employee ID, payroll, processing , income tax planning and actual deduction etc. There is seamless flow of employee data and information is available at an effectively faster rate to take appropriate decision. As custom demand increases, there is a need to meet the changing scenario with speed and efficiency. While there is a need to increase productivity, there is also a need to reduce cost of operation. The repetitive business processes can be handled effectively by automating them and freeing human resources for meeting other uncertainties. These automations not only should be done for each department, but also should cut across different departments. Thus there is a need for automating business processes at enterprise level. This enterprise level automation started with MRP, then MRP II, ERP and then finally open source ERP have taken centre stage. Out of the standard products available in the market, an organization can chose an ERP product for implementation, depending on the features available and the total cost of ownership (TCO). This comparison helps an organization to choose the product that best suits the needs for the organization. Enterprise Resource Planning: Fundamentals of Design and Implementation highlights these concepts while discusses different good practices to design and implement ERP.
Professional practice in the design and execution of employee survey programs has evolved tremendously over the past decade. Advances in technology and enthusiastic new interest in talent analytics have combined to create an exciting space with a good deal of innovation along methodological lines, matched by renewed interest in the strategic role of surveys and sensing for improving organizational effectiveness. Providing solid grounding in the basic issues of content development, interpreting results, and driving action, this book also addresses cutting-edge topics in the area of survey analytics (including applications of computational linguistics and artificial intelligence). Significant emphasis is given to ethical issues which are particularly salient given the zeitgeist for ensuring the protection of data and the privacy of survey respondents. The book is appropriate for use in advanced graduate level courses in survey research and will be a valuable shelf resource for survey practitioners whether trained formally in I-O psychology or other areas of organizational science.
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.
This book presents contributions to the 50th Annual Conference of the Operations Research Society of South Africa (ORSSA), which was jointly hosted with the African Federation of Operations Research Societies (AFROS) at North-West University in Potchefstroom, South Africa from 12 to 15 September, 2021. Focusing on innovative case studies and recent applications of Operations Research models and algorithms in African countries, each chapter highlights findings emerging from the countries in question and explains the lessons learned. As such, the book offers an up-to-date overview of Operations Research practices and developments in Africa. AFROS is a "not for profit" organization that aims to promote Operations Research in Africa. Its affairs are regulated by an Executive Committee consisting of representatives/alternates of all its member societies. The members of the Federation undertake to co-operate in the advancement of knowledge, interest and education in Operations Research by appropriate means, particularly the exchange of information, the holding of meetings and conferences, and the awarding of prizes.
This handbook includes contributions related to optimization, pricing and valuation problems, risk modeling and decision making problems arising in global financial and commodity markets from the perspective of Operations Research and Management Science. The book is structured in three parts, emphasizing common methodological approaches arising in the areas of interest: - Part I: Optimization techniques - Part II: Pricing and Valuation - Part III: Risk Modeling The book presents to a wide community of Academics and Practitioners a selection of theoretical and applied contributions on topics that have recently attracted increasing interest in commodity and financial markets. Within a structure based on the three parts, it presents recent state-of-the-art and original works related to: - The adoption of multi-criteria and dynamic optimization approaches in financial and insurance markets in presence of market stress and growing systemic risk; - Decision paradigms, based on behavioral finance or factor-based, or more classical stochastic optimization techniques, applied to portfolio selection problems including new asset classes such as alternative investments; - Risk measurement methodologies, including model risk assessment, recently applied to energy spot and future markets and new risk measures recently proposed to evaluate risk-reward trade-offs in global financial and commodity markets; and derivatives portfolio hedging and pricing methods recently put forward in the financial community in the aftermath of the global financial crisis.
This title provides managers, executives and other professionals with an innovative method for critical decision-making. The book explains the reasons for decision failures using the Law of Unintended Consequences. This account draws on the work of sociologist Robert K. Merton, psychologists Amos Tversky and Daniel Kahneman, and economist Herbert Simon to identify two primary causes : cognitive biases and bounded rationality. It introduces an innovative method for "test driving" decisions that addresses both causes by combining scenario planning and "what-if" simulations. This method enables professionals to learn safely from virtual mistakes rather than real ones. It also provides four sample test drives of realistic critical decisions as well as two instructional videos to illustrate this new method. This book provides leaders and their support teams with important new tools for analyzing and refining complex decisions that are critical to organizational well-being and survival.
This is an introduction to a flexible tool for use in strategic management within a competitive environment. Based upon ideas from both graph theory and game theory, the method offers several distinct advantages. It can handle a finite number of decision-makers, each of whom controls a number of actions. The graph model can describe and distinguish reversible and irreversible moves. Most importantly, the graph model forms a solid framework upon which solution concepts for describing human behaviour can be defined, assessed and compared This book is accompanied by a computer disk, which is explained and illustrated in the appendix. In addition, the text provides a summary of how to apply the graph model to practical problems Each chapter concludes with a set of problems, which serve to clarify important points and ensure comprehension
The Handbook of Mathematical Economics aims to provide a definitive source, reference, and teaching supplement for the field of mathematical economics. It surveys, as of the late 1970's the state of the art of mathematical economics. This is a constantly developing field and all authors were invited to review and to appraise the current status and recent developments in their presentations. In addition to its use as a reference, it is intended that this Handbook will assist researchers and students working in one branch of mathematical economics to become acquainted with other branches of this field. Volume 2 elaborates on "Mathematical Approaches to Microeconomic Theory," including consumer, producer, oligopoly, and duality theory, as well as "Mathematical Approaches to Competitive Equilibrium" including such aspects of competitive equilibrium as existence, stability, uncertainty, the computation of equilibrium prices, and the core of an economy. For more information on the Handbooks in Economics series,
please see our home page on http:
//www.elsevier.nl/locate/hes
In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and financial institutions and provide statistics to whomsoever requires them. Such analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory and focused on modelling. An understanding of time series and the application and understanding of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. Dealing with economic data involves grappling with things like varying numbers of working and trading days in different months and movable national holidays. Special attention has to be given to such things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover hidden patterns in the data and then to generate accurate forecasts. The case studies in this book demonstrate that time series adjustment methods can be efficaciously applied and utilized, for both analysis and forecasting, but they must be used in the context of reasoned statistical and economic judgment. The authors believe this is the first published study to really deal with this issue of context.
The idea of using models to inform business practice seems appealing, as it suggests the abstraction and control of a large, complex subject by means of a smaller, easily manipulated mechanism. In reality, however, many models prove inadequate when translated into business methods. Monitoring Business Performance - Models, Methods and Tools elucidates how the assumptions and perceptions that guide performance assessment are often based on models that are poor interpretations and descriptions of reality. In this book, the author scrutinizes the models underlying a number of well-known business methods and tools, and sheds light on the assumptions and subjective perceptions that undermine their effectiveness. In doing so, he offers a unique criticism of accepting business models without questioning their relevance and applicability, and highlights the need to treat models as hypotheses, rather than as certainties.
This book presents recent work that analyzes general issues of green transportation. The contributed chapters consider environmental objectives in transportation, including topics such as battery swap stations for electric vehicles, efficient home healthcare routing, waste collection, and various vehicle routing problems. The content will be valuable for researchers and postgraduate students in computer science, operations research, and urban planning.
Collateral - generally defined as an asset used to provide security for a lender's loan - is an important feature of credit contracts and all the available evidence suggests that its use is getting more pervasive. This informative book builds upon recent research into this topic. Sena analyses three case-studies that revolve around the impact that financial constraints have on economic outcomes. In the first case-study, the relationship between firms' technical efficiency and increasing financial pressure is explored. The author then goes on to show, in the second case study, that under specific circumstances, increasing financial pressure and increasing product market competition can jointly have a positive impact on firms' technical efficiency, while not being true for all types of firms. In the third case, she analyses the impact that finance constraints have on women's start-ups. Unique and revealing, this is the first book to deal so extensively with the topic of collateral, and as such, is a valuable reference to postgraduates and professionals in the fields of macroeconomics, monetary and business economics.
This book presents a general conceptual framework to translate principles of system science and engineering to service design. Services are co-created immaterial, heterogeneous, and perishable state changes. A service system includes the intended benefit to the customer and the structure and processes that accomplish this benefit. The primary focus is on the part of the service system that can reproduce such processes, called here a Service Machine, and methodological guidelines on how to analyze and design them. While the benefit and the process are designed based on the domain knowledge of each respective field, service production systems have common properties. The Service Machine is a metaphor that elicits the fundamental characteristics of service systems that do something efficiently, quickly, or repeatedly for a defined end. A machine is an artifact designed for a purpose, has several parts, such as inputs, energy flows, processors, connectors, and motors assembled as per design specifications. In case of service machine, the components are various contracts assembled on contractual frames. The book discusses Emergency Medical Services (EMS) and Emergency Departments (ED) as cases. They illustrate that service machines need to be structured to adapt to the constraints of the served market acknowledging the fact that services are co-created through the integration of producers' and customers' resources. This book is highly recommended for those who are interested in understanding the fundamental concepts of designing service machines.
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.
This is the first book focusing exclusively on fuzzy dual numbers. In addition to offering a concise guide to their properties, operations and applications, it discusses some of their advantages with regard to classical fuzzy numbers, and describes the most important operations together with a set of interesting applications in e.g. optimization, decision-making and system design. The book provides students, researchers and professionals the necessary theoretical background to apply this particular subset of fuzzy numbers to decision-making problems involving uncertainty. Further, it shows how to solve selected engineering and management problems and includes detailed numerical examples. |
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