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Author: Daniel Dolk Publisher: Springer ISBN: 3642276121 Category : Business & Economics Languages : en Pages : 319
Book Description
This book originated from several recent workshops and related activities conducted by the IFIP Working Group 7.6 on "Optimization-Based Computer Aided Modeling and Design." This group has been active for 20 years with the stated objective of developing ”high-performance computer-aided systems to support modeling, decision analysis, optimization and multi-criteria decision making.” Recently, the group has turned its attention to the application of modeling and optimization to service science, management and engineering (SSME). SSME is still a young research field searching for its theoretical underpinnings, and one which offers many opportunities for analytical modeling to not only advance the understanding, but also to help form the foundation of a new discipline. This book is the result of the group's introductory foray into the application of quantitative modeling to the nascent field of service science with special emphasis on the network aspects of services. The 11 papers presented are grouped into sections on Network Science, Comptational and Analytical Modeling, and Knowledge Science. They showcase the value of modeling in a new and timely context and provide many seeds for further exciting research.
Author: Daniel Dolk Publisher: Springer ISBN: 3642276121 Category : Business & Economics Languages : en Pages : 319
Book Description
This book originated from several recent workshops and related activities conducted by the IFIP Working Group 7.6 on "Optimization-Based Computer Aided Modeling and Design." This group has been active for 20 years with the stated objective of developing ”high-performance computer-aided systems to support modeling, decision analysis, optimization and multi-criteria decision making.” Recently, the group has turned its attention to the application of modeling and optimization to service science, management and engineering (SSME). SSME is still a young research field searching for its theoretical underpinnings, and one which offers many opportunities for analytical modeling to not only advance the understanding, but also to help form the foundation of a new discipline. This book is the result of the group's introductory foray into the application of quantitative modeling to the nascent field of service science with special emphasis on the network aspects of services. The 11 papers presented are grouped into sections on Network Science, Comptational and Analytical Modeling, and Knowledge Science. They showcase the value of modeling in a new and timely context and provide many seeds for further exciting research.
Author: Frada Burstein Publisher: Springer Science & Business Media ISBN: 3540487131 Category : Computers Languages : en Pages : 854
Book Description
Decision support systems have experienced a marked increase in attention and importance over the past 25 years. The aim of this book is to survey the decision support system (DSS) field – covering both developed territory and emergent frontiers. It will give the reader a clear understanding of fundamental DSS concepts, methods, technologies, trends, and issues. It will serve as a basic reference work for DSS research, practice, and instruction. To achieve these goals, the book has been designed according to a ten-part structure, divided in two volumes with chapters authored by well-known, well-versed scholars and practitioners from the DSS community.
Author: Daniel Power Publisher: iUniverse ISBN: 9780595787579 Category : Business & Economics Languages : en Pages : 252
Book Description
Decision Support Systems: Frequently Asked Questions is the authoritative reference guide to computerized Decision Support Systems. Author Dan Power has spent almost 30 years building, studying and teaching others about computerized Decision Support Systems. Dr. Power is first and foremost a Decision Support evangelist and generalist. From his vantage point as editor of DSSResources.COM, he tracks a broad range of contemporary DSS topics. In this DSS FAQ, Dr. Power answers 83 frequently asked questions about computerized decision support systems. The FAQ covers a broad range of contemporary topics and the questions are organized into 8 chapters. DSS FAQ helps readers understand questions like: What is a DSS? What kind of DSS does Mr. X need? Does data modeling differ for a Data-Driven DSS? Is a Data Warehouse a DSS? Is tax preparation software an example of a DSS? What do I need to know about Data Warehousing/OLAP? What is a cost estimation DSS? What is a Spreadsheet-based DSS? Decision Support Systems: Frequently Asked Questions is a useful resource for IT specialists, students, professors and managers. It organizes important Ask Dan! questions (with answers) published in DSS News from 2000 through 2004.
Author: Koen H. van Dam Publisher: Springer Science & Business Media ISBN: 9400749333 Category : Computers Languages : en Pages : 268
Book Description
Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at TU Delft and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.
Author: Management Association, Information Resources Publisher: IGI Global ISBN: 1799890244 Category : Business & Economics Languages : en Pages : 1538
Book Description
Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.
Author: Pieter Kubben Publisher: Springer ISBN: 3319997130 Category : Medical Languages : en Pages : 219
Book Description
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Author: Harvey J. Greenberg Publisher: Springer Science & Business Media ISBN: 3642835554 Category : Computers Languages : en Pages : 740
Book Description
It is quite an onerous task to edit the proceedings of a two week long institute with learned contributors from many parts of the world. All the same, the editorial team has found the process of refereeing and reviewing the contributions worthwhile and completing the volume has proven to be a satisfying task. In setting up the institute we had considered models and methods taken from a number of different disciplines. As a result the whole institute - preparing for it, attending it and editing the proceedings - proved to be an intense learning experience for us. Here I speak on behalf of the committee and the editorial team. By the time the institute took place, the papers were delivered and the delegates exchanged their views, the structure of the topics covered and their relative positioning appeared in a different light. In editing the volume I felt compelled to introduce a new structure in grouping the papers. The contents of this volume are organised in eight main sections set out below: 1 . Abstracts. 2. Review Paper. 3. Models with Multiple Criteria and Single or Multiple Decision Makers. 4. Use of Optimisation Models as Decision Support Tools. 5. Role of Information Systems in Decision Making: Database and Model Management Issues. 6. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based Systems. 7. Representation of Uncertainty in Mathematical Models and Knowledge Based Systems. 8. Mathematical Basis for Constructing Models and Model Validation.
Author: Mykel J. Kochenderfer Publisher: MIT Press ISBN: 0262331713 Category : Computers Languages : en Pages : 350
Book Description
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Author: Daniel Dolk
Author: Daniel Dolk
Author: Frada Burstein
Author: Daniel Power
Author: Koen H. van Dam
Author: Management Association, Information Resources
Author: Pieter Kubben
Author: 
Author: Harvey J. Greenberg
Author: Mykel J. Kochenderfer
Author: Efraim Turban