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Decision Making Using AI in Energy and Sustainability: Methods and Models for Policy and Practice (Applied Innovation and Technology Management)
by Gülgün Kayakutlu M. Özgür KayalicaArtificial intelligence (AI) has a huge impact on science and technology, including energy, where access to resources has been a source of geopolitical conflicts. AI can predict the demand and supply of renewable energy, optimize efficiency in energy systems, and improve the management of natural energy resources, among other things. This book explores the use of AI tools for improving the management of energy systems and providing sustainability with smart cities, smart facilities, smart buildings, smart transportation, and smart houses. Featuring research from International Federation for Information Processing's (IFIP) “AI in Energy and Sustainability” working group, this book provides new models and algorithms for AI applications in energy and sustainability fields. Any short-term, mid-term and long-term forecasting, optimization models, trend foresights and prescriptions based on scenarios are studied in the energy world and the smart systems for sustainability. The contents of this book are valuable for energy researchers, academics, scholars, practitioners and policy makers.
Decision Making with Quantitative Financial Market Data: Applications, Precautions and Pitfalls (SpringerBriefs in Operations Research)
by Alain RuttiensUse 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.
Decision Making with Spherical Fuzzy Sets: Theory and Applications (Studies in Fuzziness and Soft Computing #392)
by Cengiz Kahraman Fatma Kutlu GündoğduThis book introduces readers to the novel concept of spherical fuzzy sets, showing how these sets can be applied in practice to solve various decision-making problems. It also demonstrates that these sets provide a larger preference volume in 3D space for decision-makers. Written by authoritative researchers, the various chapters cover a large amount of theoretical and practical information, allowing readers to gain an extensive understanding of both the fundamentals and applications of spherical fuzzy sets in intelligent decision-making and mathematical programming.
Decision Making with the Analytic Network Process
by Luis G. Vargas Thomas L. SaatyThe Analytic Network Process (ANP), developed by Thomas Saaty in his work on multicriteria decision making, applies network structures with dependence and feedback to complex decision making. This new edition of Decision Making with the Analytic Network Process is a selection of the latest applications of ANP to economic, social and political decisions, and also to technological design. The ANP is a methodological tool that is helpful to organize knowledge and thinking, elicit judgments registered in both in memory and in feelings, quantify the judgments and derive priorities from them, and finally synthesize these diverse priorities into a single mathematically and logically justifiable overall outcome. In the process of deriving this outcome, the ANP also allows for the representation and synthesis of diverse opinions in the midst of discussion and debate. The book focuses on the application of the ANP in three different areas: economics, the social sciences and the linking of measurement with human values. Economists can use the ANP for an alternate approach for dealing with economic problems than the usual mathematical models on which economics bases its quantitative thinking. For psychologists, sociologists and political scientists, the ANP offers the methodology they have sought for some time to quantify and derive measurements for intangibles. Finally the book applies the ANP to provide people in the physical and engineering sciences with a quantitative method to link hard measurement to human values. In such a process, one is able to interpret the true meaning of measurements made on a uniform scale using a unit.
Decision Models in Engineering and Management
by Patricia GuarnieriProviding a comprehensive overview of various methods and applications in decision engineering, this book presents chapters written by a range experts in the field. It presents conceptual aspects of decision support applications in various areas including finance, vendor selection, construction, process management, water management and energy, agribusiness , production scheduling and control, and waste management. In addition to this, a special focus is given to methods of multi-criteria decision analysis. Decision making in organizations is a recurrent theme and is essential for business continuity. Managers from various fields including public, private, industrial, trading or service sectors are required to make decisions. Consequently managers need the support of these structured methods in order to engage in effective decision making. This book provides a valuable resource for graduate students, professors and researchers of decision analysis, multi-criteria decision analysis and group decision analysis. It is also intended for production engineers, civil engineers and engineering consultants.
Decision Options: The Art and Science of Making Decisions (Chapman & Hall/CRC Finance Series)
by Gill EapenThrough theory and case studies, this book details how uncertainty and flexibility can be evaluated to assist in making better investment decisions in companies. It delivers an excellent balance of theory and practice in the area of investment decision making, demonstrates how financial and real options are related, and describes the theoretical underpinnings of both. The author presents case studies from diverse industries, including life sciences, pharmaceuticals, commodities, energy, technology, manufacturing, and financial services. He also looks at how organizations can become successful using a holistic framework that integrates uncertainty and flexibility.
Decision Policies for Production Networks
by Dieter Armbruster Karl G. KempfThe financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain. Decision Policies for Production Networks presents recent convergent research on developing policies for operating production networks including details of practical control and decision techniques which can be applied to improve the effectiveness and economic efficiency of production networks worldwide. Researchers and practitioners come together to explore a wide variety of approaches to a range of topics including: WIP and equipment management policies, Material release policies, Machine, factory, and supply chain network policies for delivery in the face of supply and demand variability, and Conflicts between complex production network models and their controlling policies. Case studies and relevant mathematical techniques are included to support and explain techniques such as heuristics, global and hierarchical optimization, control theory and filtering approaches related to complex systems or traffic flows. Decision Policies for Production Networks acts as handbook for researchers and practitioners alike, providing findings and information which can be applied to develop methods and advance further research across production networks.
Decision Process: Five Key Steps
by Richard LueckeThis chapter illustrates how you can organize the decision-making process into five simple steps. Using these techniques reveals the pros, cons, risks, and trade-offs of any given decision.
Decision Processes by Using Bivariate Normal Quantile Pairs
by N. C. DasThis book discusses equi-quantile values and their use in generating decision alternatives under the twofold complexities of uncertainty and dependence, offering scope for surrogating between two alternative portfolios when they are correlated. The book begins with a discussion on components of rationality and learning models as indispensable concepts in decision-making processes. It identifies three-fold complexities in such processes: uncertainty, dependence and dynamism. The book is a novel attempt to seek tangible solutions for such decision problems. To do so, four hundred tables of bi-quantile pairs are presented for carefully chosen grids. In fact, it is a two-variable generalization of the inverse normal integral table, which is used in obtaining bivariate normal quantile pairs for the given values of probability and correlation. When making decisions, only two of them have to be taken at a time. These tables are essential tools for decision-making under risk and dependence, and offer scope for delving up to a single step of dynamism. The book subsequently addresses averments dealing with applications and advantages. The content is useful to empirical scientists and risk-oriented decision makers who are often required to make choices on the basis of pairs of variables. The book also helps simulators seeking valid confidence intervals for their estimates, and particle physicists looking for condensed confidence intervals for Higgs-Boson utilizing the Bose-Einstein correlation given the magnitude of such correlations. Entrepreneurs and investors as well as students of management, statistics, economics and econometrics, psychology, psychometrics and psychographics, social sciences, geographic information system, geology, agricultural and veterinary sciences, medical sciences and diagnostics, and remote sensing will also find the book very useful.
Decision Quality: Value Creation from Better Business Decisions
by Hannah Winter Jennifer Meyer Carl SpetzlerFew things are as valuable in business, and in life, as the ability to make good decisions. Can you imagine how much more rewarding your life and your business would be if every decision you made were the best it could be? Decision Quality empowers you to make the best possible choice and get more of what you truly want from every decision. Dr. Carl Spetzler is a leader in the field of decision science and has worked with organizations across industries to improve their decision-making capabilities. He and his co-authors, all experienced consultants and educators in this field, show you how to frame a problem or opportunity, create a set of attractive alternatives, identify relevant uncertain information, clarify the values that are important in the decision, apply tools of analysis, and develop buy-in among stakeholders. Their straightforward approach is elegantly simple, yet practical and powerful. It can be applied to all types of decisions. Our business and our personal lives are marked by a stream of decisions. Some are small. Some are large. Some are life-altering or strategic. How well we make those decisions truly matters. This book gives you a framework and thinking tools that will help you to improve the odds of getting more of what you value from every choice. Many people are satisfied with 'good enough' when making important decisions. This book provides a method that will take you and your co-workers beyond 'good enough' to true Decision Quality.
Decision Science (Routledge Revivals)
by Ann Van Ackere Kiriakos VlahosThis title was first published in 2000. This text is part of the "International Library of Management", which aims to present a comprehensive core reference series comprised of significant and influencial articles by the authorities in the management studies field. The collection of essays is both international and interdisciplinary in scope and aims to provide an entry point for investigating the myriad of study within the discipline.
Decision Science for Housing and Community Development
by Michael P. Johnson Armagan Bayram Senay Solak Rachel Bogardus Drew Jeffrey M. Keisler David A. TurcotteA multidisciplinary approach to problem-solving in community-based organizations using decision models and operations research applications A comprehensive treatment of public-sector operations research and management science, Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities addresses critical problems in urban housing and community development through a diverse set of decision models and applications. The book represents a bridge between theory and practice and is a source of collaboration between decision and data scientists and planners, advocates, and community practitioners. The book is motivated by the needs of community-based organizations to respond to neighborhood economic and social distress, represented by foreclosed, abandoned, and blighted housing, through community organizing, service provision, and local development. The book emphasizes analytic approaches that increase the ability of local practitioners to act quickly, thoughtfully, and effectively. By doing so, practitioners can design and implement responses that reflect stakeholder values associated with healthy and sustainable communities; that benefit from increased organizational capacity for evidence-based responses; and that result in solutions that represent improvements over the status quo according to multiple social outcome measures. Featuring quantitative and qualitative analytic methods as well as prescriptive and exploratory decision modeling, the book also includes: Discussions of the principles of decision theory and descriptive analysis to describe ways to identify and quantify values and objectives for community development Mathematical programming applications for real-world problem solving in foreclosed housing acquisition and redevelopment Applications of case studies and community-engaged research principles to analytics and decision modeling Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities is an ideal textbook for upper-undergraduate and graduate-level courses in decision models and applications; humanitarian logistics; nonprofit operations management; urban operations research; public economics; performance management; urban studies; public policy; urban and regional planning; and systems design and optimization. The book is also an excellent reference for academics, researchers, and practitioners in operations research, management science, operations management, systems engineering, policy analysis, city planning, and data analytics.
Decision Science in Action: Theory And Applications Of Modern Decision Analytic Optimisation (Asset Analytics)
by Said Salhi Madhu Jain Kusum DeepThis 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.
Decision Sciences: Theory and Practice
by Raghu Nandan Sengupta, Aparna Gupta and Joydeep DuttaThis handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.
Decision Sciences for COVID-19: Learning Through Case Studies (International Series in Operations Research & Management Science #320)
by Said Ali Hassan Ali Wagdy Mohamed Khalid Abdulaziz AlnowibetThis 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.
Decision Sourcing: Decision Making for the Agile Social Enterprise
by Dale Roberts Rooven PakkiriWe are living in the post-information age, the era of so-called 'Big Data'. It is a practical possibility for corporations to report, chart and analyse every action, transaction and click that happens inside and outside their business. In Decision Sourcing Roberts and Pakkiri examine what this means to organisational decision making. They explode the myth that good decisions need only be informed ones through an examination into how business really make choices. They lay bare the poverty of decision making processes in today’s corporate world and offer fresh and fascinating insight into how social tools are providing new sources of information, how they are challenging hierarchy and how they are providing opportunities for growth and agility through aligned and inclusive decision making. This book is for those organisations that want to get beyond the corporate Facebook account and are ready for the next bold step. It is for those businesses that want to engage their workforce and their customers in collaborative relationships that are at the heart of the successful social enterprise.
Decision Support
by David Paradice Ramesh Sharda Daniel J. Power David Schuff Frada BursteinThis volume of Annals of Information Systems will acknowledge the twentieth anniversary of the founding of the International Society for Decision Support Systems (ISDSS) by documenting some of the current best practices in teaching and research and envisioning the next twenty years in the decision support systems field. The volume is intended to complement existing DSS literature by offering an outlet for thoughts and research particularly suited to the theme of describing the next twenty years in the area of decision support. Several subthemes are planned for the volume. One subtheme draws on the assessments of internationally known DSS researchers to evaluate where the field has been and what has been accomplished. A second subtheme of the volume will be describing the current best practices of DSS research and teaching efforts. A third subtheme will be an assessment by top DSS scholars on where the DSS discipline needs to focus in the future. The tone of this volume is one of enthusiasm for the potential contributions to come in the area of DSS; contributions that must incorporate an understanding of what has been accomplished in the past, build on the best practices of today, and be be integrated into future decision making practices. The primary questions raised by this volume are: What will information systems-based decision support entail in twenty years? What research is needed to realize the envisioned future of information systems-based decision support? How will the teaching of information systems-based decision support change over the next twenty years? What are the best practices of teaching in the decision support area that can be leveraged to best disseminate DSS knowledge advances to students and practitioners?
Decision Support for Product Development: Using Computational Intelligence for Information Acquisition in Enterprise Databases (Computational Intelligence Methods and Applications)
by Marcin RelichThis book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new product development. These approaches, including artificial neural networks and constraint satisfaction solutions, enable a more precise prediction of product development performance compared to widely used multiple regression models. They support decision-makers by providing more reliable information regarding, for example, project portfolio selection and project scheduling.The book is appropriate for computer scientists, management scientists, students and practitioners engaged with product innovation and computational intelligence applications.
Decision Support System: Tools and Techniques
by Susmita BandyopadhyayThis book presents different tools and techniques used for Decision Support Systems (DSS), including decision tree and table, and their modifications, multi-criteria decision analysis techniques, network tools of decision support, and various case-based reasoning methods supported by examples and case studies. Latest developments for each of the techniques have been discussed separately, and possible future research areas are duly identified as intelligent and spatial DSS. Features: Discusses all the major tools and techniques for Decision Support System supported by examples. Explains techniques considering their deterministic and stochastic aspects. Covers network tools including GERT and Q-GERT. Explains the application of both probability and fuzzy orientation in the pertinent techniques. Includes a number of relevant case studies along with a dedicated chapter on software. This book is aimed at researchers and graduate students in information systems, data analytics, operation research, including management and computer science areas.
Decision Support System for the Location of Healthcare Facilities: SitHealth Evaluation Tool (SpringerBriefs in Applied Sciences and Technology)
by Marta Dell'Ovo Alessandra Oppio Stefano CapolongoThe book examines an integrated approach for addressing decisions about the location of healthcare facilities. Supported by Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA), the approach provides comprehensive information on territory, taking into account the spatial dimensions. Due to the multiple criteria involved, site selection for urban facilities is a crucial topic in planning decision processes, especially for healthcare facilities. Healthcare provision policies generally fail to address the distribution of facilities within cities, entrusting decisions to various stakeholders. Moreover current evaluation tools focus on the intrinsic performances of healthcare structures, disregarding the extrinsic characteristics, namely those related to the location. Starting with a cross-disciplinary literature review, the book describes a multi-methodological approach for decision-making regarding the location of healthcare facilities, and presents an innovative evaluation tool that simultaneously considers functional, locational, environmental and economic issues, providing a comprehensive overview of the areas under investigation.
Decision Support Systems For Business Intelligence
by Vicki L. SauterPraise for the First Edition "This is the most usable decision support systems text. [i]t is far better than any other text in the field" --Computing Reviews Computer-based systems known as decision support systems (DSS) play a vital role in helping professionals across various fields of practice understand what information is needed, when it is needed, and in what form in order to make smart and valuable business decisions. Providing a unique combination of theory, applications, and technology, Decision Support Systems for Business Intelligence, Second Edition supplies readers with the hands-on approach that is needed to understand the implications of theory to DSS design as well as the skills needed to construct a DSS. This new edition reflects numerous advances in the field as well as the latest related technological developments. By addressing all topics on three levels--general theory, implications for DSS design, and code development--the author presents an integrated analysis of what every DSS designer needs to know. This Second Edition features: Expanded coverage of data mining with new examples Newly added discussion of business intelligence and transnational corporations Discussion of the increased capabilities of databases and the significant growth of user interfaces and models Emphasis on analytics to encourage DSS builders to utilize sufficient modeling support in their systems A thoroughly updated section on data warehousing including architecture, data adjustment, and data scrubbing Explanations and implications of DSS differences across cultures and the challenges associated with transnational systems Each chapter discusses various aspects of DSS that exist in real-world applications, and one main example of a DSS to facilitate car purchases is used throughout the entire book. Screenshots from JavaScript® and Adobe® ColdFusion are presented to demonstrate the use of popular software packages that carry out the discussed techniques, and a related Web site houses all of the book's figures along with demo versions of decision support packages, additional examples, and links to developments in the field. Decision Support Systems for Business Intelligence, Second Edition is an excellent book for courses on information systems, decision support systems, and data mining at the advanced undergraduate and graduate levels. It also serves as a practical reference for professionals working in the fields of business, statistics, engineering, and computer technology.
Decision Support Systems IV - Information and Knowledge Management in Decision Processes: Euro Working Group Conferences, EWG-DSS 2014, Toulouse, France, June 10-13, 2014, and Barcelona, Spain, July 13-18, 2014, Revised Selected and Extended Papers (Lecture Notes in Business Information Processing #221)
by Jorge E. Hernández Fátima Dargam Shaofeng Liu Isabelle LindenThis book contains extended and revised versions of a set of selected papers from two events organized by the Euro Working Group on Decision Support Systems (EWG-DSS), which were held in Toulouse, France and Barcelona, Spain, in June and July 2014. Overall, 8 papers were accepted for publication in this edition after a rigorous review process through at least three internationally known experts from the EWG-DSS Program Committee and external invited reviewers. The selected papers focus on knowledge management and sharing, and on information models developed to support various decision processes.
Decision Support Systems IX: 5th International Conference on Decision Support System Technology, EmC-ICDSST 2019, Funchal, Madeira, Portugal, May 27–29, 2019, Proceedings (Lecture Notes in Business Information Processing #348)
by Paulo Sérgio Abreu Freitas Fatima Dargam José Maria MorenoThis book constitutes the proceedings of the 5th International Conference on Decision Support Systems Technologies, ICDSST 2019, held in Madeira, Portugal, in May 2019. This year the conference is a EURO mini conference and therefore has a slightly different acronym: "EmC-ICDSST 2019". The EWG-DSS series of International Conference on Decision Support System Technology (ICDSST), starting with ICDSST 2015 in Belgrade, was planned to consolidate the tradition of annual events organized by the EWG-DSS in offering a platform for European and international DSS communities, comprising the academic and industrial sectors, to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main topic of this year’s conference was “Main Developments and Future Trends”. The 11 papers presented in this volume were carefully reviewed and selected from 59 submissions. They were organized in topical sections named: decision support systems in societal issues; decision support systems in industrial and business applications; and advances in decision support systems’ methods and technologies.
Decision Support Systems V - Big Data Analytics for Decision Making
by Boris Delibašić Jorge E. Hernández Jason Papathanasiou Fátima Dargam Pascale Zaraté Rita Ribeiro Shaofeng Liu Isabelle LindenThis book constitutes the refereed proceedings of the First International Conference on Decision Support Systems Technology, ICDSST 2015, held in Belgrade, Serbia, in May 2015. The theme of the event was "Big Data Analytics for Decision-Making" and it was organized by the EURO (Association of European Operational Research Societies) working group of Decision Support Systems (EWG-DSS). The eight papers presented in this book were selected out of 26 submissions after being carefully reviewed by at least three internationally known experts from the ICDSST 2015 Program Committee and external invited reviewers. The selected papers are representative of current and relevant research activities in the area of decision support systems, such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluations and analysis through social networks, and decision support system applications in real-world environments. The volume is completed by an additional invited paper on big data decision-making use cases.
Decision Support Systems VII. Data, Information and Knowledge Visualization in Decision Support Systems: Third International Conference, ICDSST 2017, Namur, Belgium, May 29-31, 2017, Proceedings (Lecture Notes in Business Information Processing #282)
by Isabelle Linden, Shaofeng Liu and Christian ColotThis book constitutes the proceedings of the Third International Conference on Decision Support Systems, ICDSST 2017, held in Namur, Belgium, in May 2017. The EWG-DSS series of the International Conference on Decision Support System Technology (ICDSST) offers a platform for European and international DSS communities, comprising the academic and industrial sectors, in order to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main topic of this year’s conference was “Data, Information and Knowledge Visualization in Decision Making”. The 13 papers presented in this volume were carefully reviewed and selected from 53 submissions. They were organized in topical sections named: visualization case studies; visualization perspectives; analytics and decision; and Multi-Criteria Decision Making.