Aspiration Based Decision Support Systems: Theory, Software and Applications
The book contains contributions in the field of aspiration-led Decision Support Systems (DSS). It consists of 3 parts. Part 1 is composed of 15 theoretical papers. It starts with general papers explaining the methodological approach and the theoretical backgrounds of the methodology presented in the book. The other papers are devoted to aspects of linear programming in the context of DSS and of nonlinear model generation and manipulation for DSS and design of decision support systems for nonlinear problems. Part 2 contains six papers related to experiences in developing and using Decision Support Systems for programming development of a selected branch of chemical industry. Part 3 of the book contains short descriptions of the Decision Support Software. The software products comprise four prototype DSS for supporting various classes of decision problems, three multiple objective mathematical programming packages which can be used as components for building dedicated DSS, and an experimental version of a DSS for supporting bargaining and negotiations.
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Decision Support Systems Using
Decision Support Systems of DIDAS Family
Modern Techniques for Linear Dynamic
14 other sections not shown
achievement function algorithm alternatives applications Applied Systems Analysis approach approximation arcs aspiration levels assumed augmented Lagrangian Austria bargaining game basic calculated chemical industry coefficients column constraints corresponding criteria database Decision Analysis decision maker decision problem decision situation decision support systems defined denotes DIDAS DINAS Dobrowolski dynamic efficient outcomes efficient solutions equations evaluation feasible formulation Grauer health-care centers HYBRID IIASA implementation input Institute for Applied Interactive Decision Analysis iteration Kiwiel Kreglewski Laxenburg Lewandowski linear programming Mathematical Programming matrix maximized methodology MIDA minimized multiobjective optimization nondominated nonlinear programming objective functions objective outcomes option package parameters Pareto optimal players potential nodes programming problem reference point regularized decomposition reservation levels rows satisficing selected simplex method solving Sopron specific stochastic structure trajectory upper bounds utopia point values vector Warsaw University Wierzbicki Zebrowski