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This book includes a selection of refereed papers presented at the'Annual International Conference of the German Operations Research Society (OR2016),'which took place at the Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg, Germany, Aug. 30 - Sept. 2, 2016. Over 700 practitioners and academics from mathematics, computer science, business/economics, and related fields attended the conference. The scientific program included around 475 presentations on the theme Analytical Decision Making, focusing on the process of researching complex decision problems and devising effective solution methods towards better decisions. The book presents papers discussing classical mathematical optimization, statistics and simulation techniques. Such approaches are complemented by computer science methods and tools for the processing of data and the design and implementation of information systems. The book also examines recent advances in information technology, which allow big data volumes to be treated and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Further, it includes problems modeled and treated under consideration of uncertainty, risk management, behavioral issues, and strategic decision situations.

In two volumes, Planning Production and Inventories in the Extended Enterprise: A State of the Art Handbook examines production planning across the extended enterprise against a backdrop of important gaps between theory and practice. The early chapters describe the multifaceted nature of production planning problems and reveal many of the core complexities. The middle chapters describe recent research on theoretical techniques to manage these complexities. Accounts of production planning system currently in use in various industries are included in the later chapters. Throughout the two volumes there are suggestions on promising directions for future work focused on closing the gaps. Included in Volume 1 are papers on the Historical Foundations of Manufacturing Planning and Control; Advanced Planning and Scheduling Systems; Sustainable Product Development and Manufacturing; Uncertainty and Production Planning; Demand Forecasting; Production Capacity; Data in Production and Supply Chain Planning; Financial Uncertainty in SC Models; Field Based Research in Production Control; Collaborative SCM; Sequencing and Coordination in Outsourcing and Subcontracting Operations; Inventory Management; Pricing, Variety and Inventory Decisions for Substitutable Items; Perishable and Aging Inventories; Optimization Models of Production Planning Problems; Aggregate Modeling of Manufacturing Systems; Robust Stability Analysis of Decentralized Supply Chains; Simulation in Production Planning; and Simulation-Optimization in Support of Tactical and Strategic Enterprise Decisions. Included in Volume 2 are papers on Workload and Lead-Time Considerations under Uncertainty; Production Planning and Scheduling; Production Planning Effects on Dynamic Behavior of A Simple Supply Chain; Supply and Demand in Assemble-to-Order Supply Chains; Quantitative Risk Assessment in Supply Chains; A Practical Multi-Echelon Inventory Model with Semiconductor Application; Supplier Managed Inventory for CustomItems with Long Lead Times; Decentralized Supply Chain Formation; A Cooperative Game Approach to Procurement Network Formation; Flexible SC Contracts with Options; Build-to-Order Meets Global Sourcing for the Auto Industry; Practical Modeling in Automotive Production; Discrete Event Simulation Models; Diagnosing and Tuning a Statistical Forecasting System; Enterprise-Wide SC Planning in Semiconductor and Package Operations; Production Planning in Plastics; SC Execution Using Predictive Control; Production Scheduling in The Pharmaceutical Industry; Computerized Scheduling for Continuous Casting in Steelmaking; and Multi-Model Production Planning and Scheduling in an Industrial Environment.

This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.

This book is about elicitation: the facilitation of the quantitative expression of subjective judgement about matters of fact, interacting with subject experts, or about matters of value, interacting with decision makers or stakeholders. It offers an integrated presentation of procedures and processes that allow analysts and experts to think clearly about numbers, particularly the inputs for decision support systems and models. This presentation encompasses research originating in the communities of structured probability elicitation/calibration and multi-criteria decision analysis, often unaware of each other's developments.Chapters 2 through 9 focus on processes to elicit uncertainty from experts, including the Classical Method for aggregating judgements from multiple experts concerning probability distributions; the issue of validation in the Classical Method; the Sheffield elicitation framework; the IDEA protocol; approaches following the Bayesian perspective; themain elements of structured expert processes for dependence elicitation; and how mathematical methods can incorporate correlations between experts.Chapters 10 through 14 focus on processes to elicit preferences from stakeholders or decision makers, including two chapters on problems under uncertainty (utility functions), and three chapters that address elicitation of preferences independently of, or in absence of, any uncertainty elicitation (value functions and ELECTRE). Two chapters then focus on cross-cutting issues for elicitation of uncertainties and elicitation of preferences: biases and selection of experts.Finally, the last group of chapters illustrates how some of the presented approaches are applied in practice, including a food security case in the UK; expert elicitation in health care decision making; an expert judgement based method to elicit nuclear threat risks in US ports; risk assessment in a pulp and paper manufacturer in the Nordic countries; and elicitation of preferences for crop planning in a Greek region.

This volume collects research papers addressing topical issues in economics and management with a particular focus on dynamic models which allow to analyze and foster the decision making of firms in dynamic complex environments. The scope of the contributions ranges from daily operational challenges firms face to strategic choices in dynamic industry environments and the analysis of optimal growth paths. The volume also highlights recent methodological developments in the areas of dynamic optimization, dynamic games and meta-heuristics, which help to improve our understanding of (optimal) decision making in a fast evolving economy.

This book gathers a selection of refereed papers presented at the 4th International Symposium and 26th National Conference of the Hellenic Operational Research Society. It highlights recent scientific advances in operational research and management science (OR/MS), with a focus on linking OR/MS with other areas of quantitative methods in a multidisciplinary framework. Topics covered include areas such as business process modeling, supply chain management, organization performance and strategy planning, revenue management, financial applications, production planning, metaheuristics, logistics, inventory systems, and energy systems.

These conference proceedings focus on the topic of decision-making under uncertainty, smart decisions, management simulation and their applications in operations management for power and logistics companies. The Beijing University of Chemical Technology organized IFDS2015, the 3rd International Forum on Decision Sciences, with this year's theme being “Decision Making under Uncertainty”. The proceedings collect 7 selected papers presenting the cutting-edge modeling and solution methods and including numerous practical case studies, which are of interest for researchers and practitioners alike. Teachers, students and practitioners working in the fields of decision science, operations research, management science and engineering will benefit from the valuable findings presented in this book.

The purpose of this book is to introduce and explain research at the boundary between two fields that view problem solving from different perspectives. Researchers in operations research and artificial intelligence have traditionally remained separate in their activities. Recently, there has been an explosion of work at the border of the two fields, as members of both communities seek to leverage their activities and resolve problems that remain intractable to pure operations research or artificial intelligence techniques. This book presents representative results from this current flurry of activity and provides insights into promising directions for continued exploration. This book should be of special interest to researchers in artificial intelligence and operations research because it exposes a number of applications and techniques, which have benefited from the integration of problem solving strategies. Even researchers working on different applications or with different techniques can benefit from the descriptions contained here, because they provide insight into effective methods for combining approaches from the two fields. Additionally, researchers in both communities will find a wealth of pointers to challenging new problems and potential opportunities that exist at the interface between operations research and artificial intelligence. In addition to the obvious interest the book should have for members of the operations research and artificial intelligence communities, the papers here are also relevant to members of other research communities and development activities that can benefit from improvements to fundamental problem solving approaches.

This book contains an edited selection of papers presented at the Eighth Research Conference on Subjective Probability, Utility and Decision Making, held in Budapest. Together they span a wide range of new developments in studies of decision making, the practice of decision analysis and the development of decision-aiding technology.The volume is arranged in sections: Societal Decision Making; Organizational Decision Making; Aiding the Structuring of Small Scale Decision Problems, and Tracing Decision Processes.The emphasis is on decision processes and structures and their applications, rather than formal modelling in isolation, thus reflecting current developments in research and practice which follow from the understanding of the nature and operation of decision theoretical models gained during the 1970's.The fifth section, A Symposium on the Validity of Studies on Heuristics and Biases, is of a different nature. The papers take stock of the considerable volume of work investigation ``heuristics and biases''in decision making over the past decade, and their implication for theory and practice.

This book deals with an often-neglected feature of location problems, namely uncertainty, by combining two related fields: location theory and optimization. Written by leading researchers and practitioners in these fields, each chapter examines one aspect of the location process in different contexts, such as supply chains; location decisions under congestion; disaster management; design of resilient facilities; uncertainty in the health sector; and facility location in the retail sector under uncertainty. The book also addresses methodological aspects, such as chance-constrained approaches, heuristic algorithms, scenario approaches, and simulation. As such, it provides decision-makers with essential methods, tools and approaches to help them deal with these uncertainties. It is mainly intended for graduate students in the fields of operations research and logistics, as well as professionals in logistics and supply chain management.

This book examines how people make decisions under risk and uncertainty in operational settings and opens the black box by specifying the cognitive processes that lead to human behavior. Drawing on economics, psychology and artificial intelligence, the book provides an innovative perspective on behavioral operations. It shows how to build optimization as well as heuristic models for describing human behavior and how to compare such models on various dimensions such as predictive power and transparency, as well as discussing interventions for improving human behavior. This book will be particularly valuable to academics and practitioners who seek to select a modeling approach that suits the operational decision at hand.

Principles of External Business Environment Analyzability in an Organizational Context, by Bruno F. Abrantes, is a groundbreaking work on the topic of business environmental analysis (BEA) within strategic management. Abrantes provides a comprehensive overview of the evolution of management theory, narrowing the focus to organizational management and strategic management, and delving into the intricacies of business environments. He introduces the tenets of philosophy of management and analyzability, exploring a wide range of analytical models and decision-making strategies, and offering over 50 models applicable to BEAP, along with suggestions for an additional 50 models for decision- making and project management. This book is an essential resource for university and college students in business, economics, and marketing, particularly those taking a strategic management course. It provides a deep understanding of BEAP design and a critical sense for the philosophical questions behind analyzability in decision- making. Moreover, it is a valuable reference source for management consultants and strategists looking to expand their horizons beyond their department or consultancy company. Topics covered in the book include black swans, environmental forecasting, future thinking, scenario planning, VUCA, and wild card, among others. Principles of External Business Environment Analyzability in an Organizational Context is a must-read for anyone seeking to excel in the critical field of business environmental analysis.

This book contributes to the theoretical discussions of equilibria that rest on error―in which we include mistaken choices of games to play. Extant game theory recommends diverse strategies (plans of actions) for various given games, particularly those in Nash equilibria, in which no player benefits from one-sided strategy alteration. The literature also refers to the design of games that fit given goals. This is the mechanism design theory; its function is to serve social planners ignorant of the preferences of the people intended to play them.Our study of games avoidance adds to game theory the meta-game of choosing what game to play and what game to avoid playing, and that both players and planners can generate. This comprises a shift from the maximalist position that aims to maximize possible profit to the minimalist one that aims at minimizing possible loss. This shift depends on the question, considering the public interest, what set of games is it advisable to encourage? Obviously, it is advisable to encourage playing some groups of games such as trade, as well as to discourage playing other groups of games such as wars. This shift makes the theory much more applicable to social science: usually, choosing what game to play is less practical than choosing what game not to play. This invites legislation and similar incentives; their study should aim at the improvement of their usefulness.Discussing the possibility of changing both game and strategy renders game theory part-and-parcel of social science. For this mathematical models will not do: it requires a clear distinction between describing options and explaining situations. Explanations may enhance efforts at improvement.

This book provides a blend of quantitative and qualitative approaches to decision making, while also bridging the gap between the theory of how to make good decisions versus how people actually make decisions. The authors present the tools and techniques of decision analysis to learn how to become a FOCCUSSED decision maker: Identify and properly Frame the decision or problem at handSpecify the goals, Objectives, and values that you are trying to achieveDevelop creative, meaningful Choices from among which you can chooseEvaluate the Consequences of selecting each alternative using your goals, objectives, and valuesThink about the key Uncertainties that could impact the decisionUnderstand the Swaps and trade-offs that you are willing to makeDevelop an approach for implementing your SolutionElicit the data you'll need from a variety of sourcesand Disseminate and communicate your decisions to others. The authors define a decision as the choice among alternatives, based on how we value and trade-off their pros and cons, made in the face of uncertainty about what will actually happen. The decision-making process is presented as having three pillars to support the decision maker: Preferences–what we prefer, what meets our goals and objectives, and the recognition that preferences are personal to the one making the decision; Alternatives–the choices, options, or courses of action that we have, and over which we have some degree of control; and Information–what we know about the situation, what we don't know, how we connect choices to outcomes, and how we deal with uncertainty. Key components of good decision-making include how to define your goals and objectives, how to incorporate uncertainties that we all face, and how to develop better alternatives, all of which are discussed. Sophisticated techniques are presented in a way that is accessible to the average decision maker. Probability theory is utilized to improve decisions, and uncertainties are captured in decision trees. Risk avoidance, risk transfer, and risk mitigation are also discussed. Readers will gain a clear understanding of how to articulate the goals and objectives that should be the focal point of any decision.

This book covers sustainable development in smart society's 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.

This book proposes a new approach to dynamic and online risk assessment of automated and autonomous marine systems, taking into account different environmental and operational conditions. The book presents lessons learnt from dynamic positioning incidents and accidents, and discusses the challenges of risk assessment of complex systems. The book begins by introducing dynamic and online risk assessment, before presenting automated and autonomous marine systems, as well as numerous dynamic positioning incidents. It then discusses human interactions with technology and explores how to quantify human error. Dynamic probabilistic risk assessment and online risk assessment are both considered fully, including case studies with the application of assisting operators in decision making in emergency situations. Finally, areas for future research are suggested. This practical volume offers tools and methodologies to help operators make better decisions and improve the safety of automated and autonomous marine systems. It provides a guideline for researchers and practitioners to perform dynamic probabilistic and online risk assessment, which also should be applicable to other complex systems outside the marine and maritime domain, such as nuclear power plants, chemical processes, autonomous transport systems, and space shuttles.

Applications of Management Science showcases current studies in the application of management science, contributing to the solution of significant managerial decision-making problems. To those involved in the applications of multi-criteria decision making, data envelopment analysis, and decision making, in a realistic managerial problem-solving environment through the use of state-of-the-art management science modeling, this is a must read. The research presented by academics in Volume 13 significantly aids in the deconstruction of managerial decision-making problems with management science methodologies. Specifically focusing on the applications of management science methodologies data envelopment analysis and multi-criteria decision making, this collection is split into three sections: Data Envelopment Analysis, Optimization Modeling, Business Analytical Modeling. Applications of Management Science is core for those academics, researchers, and practitioners of management science in mitigating significant managerial decision-making problems, for both the public and the private sectors.

This book presents a consistent methodology for making decisions under uncertain conditions, as is almost always the case. Tools such as value of information and value of flexibility are explored as a means to make more complex and nuanced decisions.The book develops the complete formalism for assessing the value of acquiring information with two novel approaches. Firstly, it integrates the fuzzy characteristics of data, and secondly develops a methodology for assessing data acquisition actions that optimize the value of projects from a holistic perspective. The book also discusses the formalism for including flexibility in the project decision assessment. Practical examples of oil- and gas-related decision problems are included and discussed to facilitate the learning process.This book provides valuable advice and case studies applicable to engineers, researchers, and graduate students, particularly in the oil and gas industry and pharmaceutic industry.

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises'productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.

This book examines inventory and production strategies that can reduce unexpected breakdown costs. It highlights different EPQ models to deal with such problems, providing optimal value derivations for decision variables. It provides proofs for concavity or convexity of objective functions. The chapters also include numerical examples for all the developed mathematical models. Imperfect Inventory Systems: Inventory and Production Management and Breakdown should be useful for professionals working on supply chains, but also researchers in operations research and inventory management.

This book is the second edition of Behavioral Decision Theory, published in 2014. The main approach and structure of this book have been retained in the new edition. However, this second edition provides a fresh overview of the idea of behavioral decision theory and related research findings such as theoretical and empirical discoveries of preference formation, time discounting, social interaction, and social decision making. The book covers a wide range from classical to relatively recent major studies concerning behavioral decision theory, which, in brief, is a general term for descriptive theories to explain the psychological knowledge related to people's decision-making behavior. It is called a theory but is actually a combination of various psychological theories, for which no axiomatic systems—such as those associated with the utility theory widely used in economics—have been established.The utility theory is often limited to qualitative knowledge;however, as the studies of Nobel laureates H. A. Simon, D. Kahneman, and R. Thaler have suggested, the psychological methodology and knowledge of behavioral decision theory have been applied widely in such fields as economics, business administration, and engineering and are expected to become even more useful in the future. Research into people's decision making represents an important part in those fields, various aspects of which overlap with the scope of behavioral decision theory. This theory is closely related to behavioral economics and behavioral finance, which have come into greater use in recent years. This book will appeal especially to graduate students, advanced undergraduate students, and researchers who are interested in decision-making phenomena.

Use of quantitative data, especially in financial markets, may provide rapid results due to the ease-of-use and availability of fast computational software, but this book advises caution and helps to understand and avoid potential pitfalls.It deals with often underestimated issues related to the use of financial quantitative data, such as non-stationarity issues, accuracy issues and modeling issues. It provides practical remedies or ways to develop new calculation methodologies to avoid pitfalls in using data, as well as solutions for risk management issues in financial market. The book is intended to help professionals in financial industry to use quantitative data in a safer way.

The book covers the domain of multi-criteria decision making, a topic which has gained significant attention of researchers and practitioners spanning a variety of disciplines for enhancing their decision making in real life situation. The topics in this volume help readers understand the techniques in the model building and analysis stage. The chapters cover a variety of techniques and their applications for interesting problems. This book will be of interest to readers in diverse disciplines such as engineering, business, management, humanities, psychology and law. ^

This book contains international perspectives that unifies the themes of strategic management, decision theory, and data science. It contains thought-provoking presentations of case studies backed by adequate analysis adding significance to the discussions. Most of the decision-making models in use do take due advantage of collection and processing of relevant data using appropriate analytics oriented to provide inputs into effective decision-making. The book showcases applications in diverse fields including banking and insurance, portfolio management, inventory analysis, performance assessment of comparable economic agents, managing utilities in a health-care facility, reducing traffic snarls on highways, monitoring achievement of some of the sustainable development goals in a country or state, and similar other areas that showcase policy implications. It holds immense value for researchers as well as professionals responsible for organizational decisions.

This book offers an introduction to various models and methods for green supplier evaluation and selection (GSES) within different information settings. As such, it provides valuable knowledge, useful GSES methods and practical examples that can be considered by manufacturers in selecting appropriate green suppliers to improve their environmental performance and customer satisfaction. This book is useful for practitioners and researchers working in the fields of supply chain management, operation management, information science, industrial engineering, and management science. It is also useful as a textbook for postgraduate and senior undergraduate students.

This book analyses decision-making in dynamic economic environments. By applying a wide range of methodological approaches, combining both analytical and computational methods, the contributors examine various aspects of optimal firm behaviour and relevant policy areas. Topics covered include optimal control, dynamic games, economic decision-making, and applications in finance and economics, as well as policy implications in areas such as pollution regulation. This book is dedicated to Christophe Deissenberg, a well-known and distinguished scholar of economic dynamics and computational economics. It appeals to academics in the areas of optimal control, dynamic games and computational economics as well as to decision-makers working in policy domains such as environmental policy.

An important activity for an organization's leaders and managers is making decisions associated with problem-solving. Making decisions is a complex endeavor where choices are made from courses of action where resources are limited and in the presence of constraints. Written as a guide, this book offers a quantitative approach to decision-making.The process of decision-making is presented from a holistic point of view. This book offers a basic understanding of the issues and processes involved in decision-making by presenting the tools associated with problem analysis, tools that enable developing choices, as well as tools used to normalize judgment criteria achievement so that they are comparable across measures using different scales. Several solution methods for decision problems that have one evaluation criterion are explained first. Methods for problems with multiple criteria for evaluating alternate solutions are discussed as well. The multiple criteria methods include those that do not require any explicit preference or trade-off information from the decision-maker and those that do require the decision-maker's preference or trade-off information.The intended audience of the book includes technical and nontechnical professionals, managers, and supervisors at all levels, and engineering and business educators. The book would also be useful to undergraduate students, beginning graduate students, and recent graduates of professional programs, or in mathematics, computer science, natural sciences, and humanities.

This book illustrates the importance effective cost management systems inproviding a supportive environment in which reliable and relevant managementinformation can be generated. Such a cost management system is only attainableif the importance of key business, operational and stakeholder requirements arerecognised within the organisational context. In illustrating this importance, thisbook provides several case studies as examples thereof. The first two case studiesfocus on the engineering sector and illustrates the development of a costmanagement system in a water recycling context; and the design of a budgetarysystem in a mining engineering context. The remaining case studies focus on theservices sector, including cost management systems for a digital technologyservices provider and a medical insurance services provider; an alternativeactivity-based costing approach for a public sector services provider; and finallya re-designed value stream for an automotive services provider. Academicresearchers and industry managers in the fields of management accounting andfinancial management, as well as engineering and operations management, willfind value in the experiences described herein.

Over the last fifty years advanced mathematical tools have become an integral part in the development of modern economic theory. Economists continue to invoke sophisticated mathematical techniques and ideas in order to understand complex economic and social problems. In the last ten years the theory of Riesz spaces (vector lattices) has been successfully applied to economic theory. By now it is understood relatively well that the lattice structure of Riesz spaces can be employed to capture and interpret several economic notions. On April 16-20, 1990, a small conference on Riesz Spaces, Positive Opera­ tors, and their Applications to Economics took place at the California Institute of Technology. The purpose of the conference was to bring mathematicians special­ ized in Riesz Spaces and economists specialized in General Equilibrium together to exchange ideas and advance the interdisciplinary cooperation between math­ ematicians and economists. This volume is a collection of papers that represent the talks and discussions of the participants at the week-long conference. We take this opportunity to thank all the participants of the conference, especially those whose articles are contained in this volume. We also greatly ap­ preciate the financial support provided by the California Institute of Technology. In particular, we express our sincerest thanks to David Grether, John Ledyard, and David Wales for their support. Finally, we would like to thank Susan Davis, Victoria Mason, and Marge D'Elia who handled the delicate logistics for the smooth running of the confer­ ence.

This book presents a range of qualitative and quantitative analyses in areas such as cybersecurity, sustainability, multivariate analysis, customer satisfaction, parametric programming, software reliability growth modeling, and blockchain technology, to name but a few. It also highlights integrated methods and practices in the areas of machine learning and genetic algorithms. After discussing applications in supply chains and logistics, cloud computing, six sigma, production management, big data analysis, satellite imaging, game theory, biometric systems, quality, and system performance, the book examines the latest developments and breakthroughs in the field of science and technology, and provides novel problem-solving methods. The themes discussed in the book link contributions by researchers and practitioners from different branches of engineering and management, and hailing from around the globe. These contributions provide scholars with aplatform to derive maximum utility in the area of analytics by subscribing to the idea of managing business through system sciences, operations, and management. Managers and decision-makers can learn a great deal from the respective chapters, which will help them devise their own business strategies and find real-world solutions to complex industrial problems.

This book advances systems thinking by introducing a new philosophy of systemic knowing. It argues that there are inescapable limits to rational understanding. Humankind has always depended on extended ways of knowing to complement the rational-analytic approach. The book establishes that the application of such methods is fundamental to systemic practice. The author advocates embracing two modes of consciousness: intentionality, which Western philosophy has long recognized, and non-intentional awareness, which Eastern philosophy additionally highlights. The simultaneity of these two modes of consciousness, and the variety of knowings they spawn are harnessed for a more holistic, systemic knowing. Four practices from fields related to systems thinking are examined: two contemporary action research methodologies from the US and the UK; the Sumedhian (Indian) approach to inquiry about processes within groups; and a technique of group psychotherapy originating in Eastern Europe. Each of these systematically harnesses knowing using both modes of consciousness. Therefore, the author insists, such approaches must be included in systemic practice, in purposeful and methodical juxtaposition to rational-analytic ways. The book provides examples and guidelines for deployment.“All researchers and practitioners of systems thinking and action research must read this book...Raghav has craftfully blended Eastern and Western wisdom. He uses his immersion into Eastern ways of knowing practically, to elaborate the systems philosophy in rich detail. He has incorporated, from cooperative inquiry as action research, the idea of four ways of knowing: practical, propositional, presentational and experiential, to bolster the foundations of systems thinking”―SHANKAR SANKARAN, Professor, University of Technology Sydney, Australia; President International Society of Systems Sciences (ISSS) 2019-2020“This is a book with the potential to stimulate the emergence of a new paradigm. Raghav shows that systems thinking can transcend rational analysis and incorporate other ways of knowing, such as arts-based methods… also, rather than be overly preoccupied with striving for change, there is value in simply abiding, which comes with a deep appreciation of the ecological relationships we are part of. It's not that rational analysis is wrong – it's that it is only part of a genuinely transformative practice”. ―GERALD MIDGLEY, Co-Director, Centre for Systems Studies, University of Hull; former President, ISSS (2013-14)“Raghav Rajagopalan's writing on generating deep appreciation for the social and ecological interdependencies ties in closely with my own work. The philosophical ideas he develops contain the tracings and essential tones of Gregory Bateson's idea of'Mind'as a process of living complexities reaching well beyond the notion of the body. This book demonstrates outstanding erudition and deep compassion at the same time. It should delight the adventurous reader unafraid of big questions”.―NORA BATESON, President of the International Bateson Institute

Seaport Container Terminals (SCT) operate as central nodes in worldwide hub-and-spoke networks, and link ocean-going vessels with smaller feeder vessels, as well as with inbound and outbound hinterland transportation systems using road, rail, or inland waterways. The volume of transcontinental container flows has gained enormously over the last five decades frequently leading to double-digit annual growth rates for the SCT. The 2nd edition of the Handbook of Terminal Planning also deals with problems being induced by questions of terminal development on a long-term basis (strategic level). Facing present and upcoming challenges for SCT operation—such as more and more mega vessels, extremely high hinterland peaks, higher environmental standards, less public acceptance and the stronger competition between terminals serving the same hinterland—the focus of the book is on successful approaches and solutions primarily addressing the planning of terminal structures. Nevertheless, operational aspects are considered, as well as how they effectively contribute to problem solving on the strategic level.

This book focuses on operations management methods for analysing complex systems from a system engineering perspective. It presents various advanced multi-criteria decision analysis methods for investigating factors that influence complex systems. In turn, it shows how to improve systems'performance, including their competitiveness, safety, and sustainability. The book also draws on examples of typical virtual systems such as tourism, aviation maintenance, and waste-to-wealth systems to illustrate the operations management methods discussed. Cases from day-to-day life are used to elicit heuristic questions on the operations management methods presented in each chapter. The book will help researchers, operations managers, and engineers alike to understand the latest advances in operations management methods for analysing complex systems from the standpoint of system engineering.

Strategy, risk management and project management are often considered separately by those applying their principles—but at their most effective, all are dependent upon each other for success. Enlightened Planning teaches this holistic perspective and demonstrates how a synthesis of these approaches yields far greater opportunities. A strategic, calculated risk, for example, can be less inherently risky than chronic risk aversion over time. Here, a respected specialist and teacher demonstrates how to become an'enlightened planner', one that is aware of project, strategy and risk concerns, and their potential interplay. Following the core principle of Keep It Simple Systematically, he shows how organised, systematic thought processes can demystify the complexities of decision-making when considering a huge variety of concerns at once. Supported throughout with real-life cases from the author's considerable experiences with commercial organisations, it is also supported by a website containing even more cases, learning and teaching materials. This book is essential reading for any practitioner specialising in risk management, project management or strategy; as well as those teachers or participants in executive programmes.

This book develops a general theory of managerial decision making on the basis of a few elementary postulates. It employs logic as the method of reasoning, systems science in general and the systemic YoYo Model in particular, as the intuitive playground. By doing so, the authors take individually background-based guesswork out of processes of decision making. All established conclusions are expected to be generally employable in real-life applications. At the same time, the book is user friendly to a wide range of audience, coincides with people's intuition, and provides applicable results and insights for practical purposes.

This book presents the multi-criteria approach to decision support, as well as the various multi-criteria tools to help avoid multi-objective optimization. The book is intended as a tool for understanding the multi-criteria tools for decision support and modeling in mathematical programming. It helps to structure models, to easily model complex constraints, to have a basic modeling guide for any multi-criteria system and to better understand models already existing in the literature.The book is structured in the same order as components of the methodology, established in a multi-criteria optimization problem. It introduces the elements of the actors, the decision-making activity under criteria, calculations, specifications and objective criterion.

This book offers a comprehensive introduction to decision-making in an MCDM framework. Designed as a tutorial, it presents the main concepts and methods to be applied, together with essential background information. This includes the concept of nondominance, Simon's bounded rationality, Tversky and Kahneman's prospect theory, and the concepts of behavioral vs. mathematical convergence and premature stopping put forward by Korhonen, Moskowitz and Wallenius. The book concludes with a non-technical review of many popular decision algorithms, including the Analytic Hierarchy Process (AHP), VIMDA, and a number of classic interactive man-machine algorithms. In essence, the book is a “one-stop” source on everything you need to know about managerial decision-making in the multiple-criteria setting.

This book discusses how to build optimization tools able to generate better future studies. It aims at showing how these tools can be used to develop an adaptive learning environment that can be used for decision making in the presence of uncertainties. The book starts with existing fuzzy techniques and multicriteria decision making approaches and shows how to combine them in more effective tools to model future events and take therefore better decisions. The first part of the book is dedicated to the theories behind fuzzy optimization and fuzzy cognitive map, while the second part presents new approaches developed by the authors with their practical application to trend impact analysis, scenario planning and strategic formulation. The book is aimed at two groups of readers, interested in linking the future studies with artificial intelligence. The first group includes social scientists seeking for improved methods for strategic prospective. The second group includes computer scientists and engineers seeking for new applications and current developments of Soft Computing methods for forecasting in social science, but not limited to this.

This book examines cross-chain control centers (4C), an ambitious concept in supply chain management and logistics that is intended to foster collaboration between different supply chains to increase efficiency. It provides an overview of the main results, insights, and other developments in the academic field of horizontal collaboration. Furthermore, it gives recommendations to governments, commercial companies, and academia on how to proceed with horizontal logistics collaboration in the years to come. To link research with practice, the book takes the Dutch project on cross-chain collaboration centers (4Cs) and identifies a typology of existing patterns for horizontal collaboration in supply chains. Finally, the book zooms in on the Netherlands as a case-study of intense public-private partnerships to develop 4C as a mature logistics value proposition. It provides an overview of the accomplishments in the government supported 4C projects and offers a critical reflection of why some more ambitious and structural solutions have not found solid ground yet. The book is of value to researchers and professionals in the supply chain domain.

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.

With contributions from some of the top academics and scientists in the field, Advanced Studies in Multi-Criteria Decision Making presents an updated view of the landscape of Decision Sciences, current research topics, the interaction with other sciences and fields, as well as the prospects and challenges at an international level. Given that Decision Sciences are recognized today as indispensable for confronting the major societal challenges in science and technology, this book would be of interest to decision-makers, managers, and researchers from academia, and industrial/services companies that would like a fresh insight into MCDM.Features Integrates a wide range of scientific fields with a general reader approach, including applied researchers from the social, business, enterprise sciences Suitable for academics and professionals Presents a broad coverage of MCDM tools either in industry or in services companies and systems Provides a fresh overview on MCDM studies promoted by prestigious R&D institutions

This edited collection addresses the question of which capabilities and competencies enable Behavioral Operational Research to provide sustained improvement to decision processes. The aim is to show how a focus on capability and competency will not only meet short-term requirements for problem solving and decision support, but also build a solid foundation for the future. The contributors present recent advances in Behavioral OR, with a focus on the ways in which users of models deal with incomplete and imprecise information, subjective boundaries and uncertainty. These chapters are structured around three key dimensions of BOR: capabilities, cognition and aspects of practice.

This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards.In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.

This book examines relationships between pairwise comparisons matrices. It first provides an overview of the latest theories of pairwise comparisons in decision making, discussing the pairwise comparison matrix, a fundamental tool for further investigation, as a deterministic matrix with given elements. Subsequent chapters then investigate these matrices under uncertainty, as a matrix with vague elements (fuzzy and/or intuitionistic fuzzy ones), and also as random elements. The second part of the book describes the application of the theoretical results in the three most popular multicriteria decision-making methods: the Analytic Hierarchy Process (AHP), PROMETHEE and TOPSIS. This book appeals to scholars in areas such as decision theory, operations research, optimization theory, algebra, interval analysis and fuzzy sets.

This textbook covers the fundamental mechanisms of the Six Sigma philosophy, while showing how this approach is used in solving problems that affect the variability and quality of processes and outcomes in business settings. Further, it teaches readers how to integrate a statistical perspective into problem solving and decision-making processes. Part I provides foundational background and introduces the Six Sigma methodology while Part II focuses on the details of DMAIC process and tools used in each phase of DMAIC. The student-centered approach based on learning objectives, solved examples, practice and discussion questions is ideal for those studying Six Sigma.

This book presents essential information on modern location science – in a word, all you need to know about location. The second edition of this handbook has been fully revised throughout, with numerous updates and chapters added, to offer an even more comprehensive overview of methods and applications. The book is divided into three parts: basic concepts, advanced concepts and applications. Written by the most respected specialists in the field and thoroughly reviewed by the editors, it first lays out the fundamental problems in location science and provides readers with basic background information on location theory. Part II covers advanced models and concepts, broadening and expanding on the content presented in Part I. It also discusses important tools to help readers grasp and solve real-world location problems. Part III focuses on the links between location science and other areas like GIS, telecommunications, healthcare, rapid transit networks, districting problems and disaster events, and presents a wide range of applications to allow readers to understand the role of facility location in such areas and learn how to handle real-world location problems. The book is intended for researchers working on theory and applications involving location problems and models. It is also suitable as a textbook for graduate courses on facility location.

This book presents 27 methods of the Multiple Attribute Decision Making (MADM), which are not discussed in the existing books, nor studied in details, using more applications. Nowadays, decision making is one of the most important and fundamental tasks of management as an organizational goal achievement that depends on its quality. Decision making includes the correct expression of objectives, determining different and possible solutions, evaluating their feasibility, assessing the consequences, and the results of implementing each solution, and finally, selecting and implementing the solution. Multiple Criteria Decision Making (MCDM) is sum of the decision making techniques. MCDM is divided into the Multiple Objective Decision Making (MODM) for designing the best solution and MADM for selecting the best alternative. Given that the applications of MADM are mostly more than MODM, wide various techniques have been developed for MADM by researchers over the last 60 years, and the currentbook introduces some of the other new MADM methods.

This book considers and builds on the main propositions regarding body similarity and the principles of nature versus artifacts in science. It also explores the design (matrix) power of the human, Material/Machine, Money & Information (3M&I) body with respect to productivity/gross domestic product (GDP). The book begins in 2009 with Weiner's cybernetics and describes Matsui's theory and dynamism concerning the basic equation of W = ZL and artifact formulation using matrix methods, such as Matsui's matrix equation (Matsui's ME). In his book Fundamentals and Principles of Artifacts Science: 3M&I-Body System, published by Springer in 2016, the author championed the white-box approach for 3M&I artifacts in contrast to Simon's artificial approach from 1969. Two principles, the Sandwich (waist) and Balancing theories, and their fundamental problems, were identified. This book now proposes a third principle: the fractal/harmonic-like structure of the cosmos and life types in space and time. The book further elaborates on the complexity of the 3M&I system and management in terms of enterprises, economics, nature, and other applications. Also, the domain of nature versus artifacts is highlighted, demonstrating the possibility of a white-box cybernetics-type robot. This fosters the realization of humanized and harmonic worlds that combine increased happiness and social productivity in an age increasingly dominated by technology.

This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems. The book's twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja–Bretones–Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes. Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot's stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem. The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few.

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book's chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.