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Decision Support Systems (DSS) have been identified as a solution to the military commander's needs for information filtering and analysis. Current literature on the theory and techniques of DSS design have been addressed to the decision-making processes of commercial applications. The lack of a comprehensive treatment of military command and control decision-making requirements may result in a number of command and control DSS which are not designed for the reliability and flexibility required in a context of everchanging threats. This thesis is an initial attempt to identify some unique considerations for the design of a command and control decision support system and offers suggestions towards the development of flexible, reliable systems to serve commanders in both peacetime and combat operations. (Author).
Decision Support Systems (DSS) have been identified as a solution to the military commander's needs for information filtering and analysis. Current literature on the theory and techniques of DSS design have been addressed to the decision-making processes of commercial applications. The lack of a comprehensive treatment of military command and control decision-making requirements may result in a number of command and control DSS which are not designed for the reliability and flexibility required in a context of everchanging threats. This thesis is an initial attempt to identify some unique considerations for the design of a command and control decision support system and offers suggestions towards the development of flexible, reliable systems to serve commanders in both peacetime and combat operations. (Author).
The focus of Decision Support Systems is on how one can & should use what has been learned in programming & modeling courses to develop systems that provide decision support. Pages on the World Wide Web will be available to support this book.
The rapidly developing technology of command and control and decision support systems requires improvement in the way the human element is integrated into the system. The limitation of human cognitive capacity must not be exceeded, or the system will fail. A properly designed decision support system should include provision for the heuristics that are likely to be employed by a decision maker when faced with a rapidly changing and and information intensive situation and incomplete or questionable data. Many measures to effectiveness have bee proposed for battle management and C2 systems. In this paper, where system consist of an integrated combination of a human decision maker and his decision support system, three measures of effectiveness are proposed and discussed. Improvements in performance of the total system can be made by improving the efficiency of information exchange between the DM and the support system. The KOALAS architecture has been shown to be an effective implementation of a simulation and rule based expert system which can increase the efficiency of information exchange between the human decision maker and the decision support system. Potential improvements in KOALAS' architecture are discussed with recommendations for improving its employment and utility.
A selective review of modern decision science and implications for decision-support systems. The study suggests ways to synthesize lessons from research on heuristics and biases with those from "naturalistic research." It also discusses modern tools, such as increasingly realistic simulations, multiresolution modeling, and exploratory analysis, which can assist decisionmakers in choosing strategies that are flexible, adaptive, and robust.
This book presents real-world decision support systems, i.e., systems that have been running for some time and as such have been tested in real environments and complex situations; the cases are from various application domains and highlight the best practices in each stage of the system’s life cycle, from the initial requirements analysis and design phases to the final stages of the project. Each chapter provides decision-makers with recommendations and insights into lessons learned so that failures can be avoided and successes repeated. For this reason unsuccessful cases, which at some point of their life cycle were deemed as failures for one reason or another, are also included. All decision support systems are presented in a constructive, coherent and deductive manner to enhance the learning effect. It complements the many works that focus on theoretical aspects or individual module design and development by offering ‘good’ and ‘bad’ practices when developing and using decision support systems. Combining high-quality research with real-world implementations, it is of interest to researchers and professionals in industry alike.
As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come.