Multiple Criteria Decision Support in Engineering DesignMultiple Criteria Decision Support in Engineering Design examines some of the underlying issues and related modelling strategies, with a view to exploring the rich potential of a generalised multiple-criteria approach to design decision-making. The arguments are supported by numerical examples. It can be argued that, within the classic monocriterion paradigm, the optimal solution is inarguably identified once the feasible alternatives are established and an objective function agreed on. It is only when conflict resolution is involved that decision-making truly becomes important, and many design situations exist where stated functional requirements may be in actual or potential conflict. The most preferred solution under such circumstances depends on the designer's or decision-maker's priorities, so that the chosen solution is based on a combination of technical possibilities and designer preferences. This book addresses the key concepts in multiple criteria decision-making and provides valuable insight into how such problems arise and can be solved, in the area of decision-making in general and in the domain of engineering design in particular. |
Contents
Foreword | 1 |
Multiple Attribute Decision Making | 19 |
Multiple Objective Decision Making | 113 |
Copyright | |
5 other sections not shown
Other editions - View all
Multiple Criteria Decision Support in Engineering Design Pratyush Sen,Jian-Bo Yang Limited preview - 2012 |
Multiple Criteria Decision Support in Engineering Design Pratyush Sen,Jian-Bo Yang No preview available - 2011 |
Common terms and phrases
a₁ Amax analysis choice CODASID method Comparison Matrix computational concordance index cost criterion decision maker decision matrix decision problem decision support system decrement of objective defined design variables dominated efficient designs efficient solutions eigenvector engineering design example factors feasible Gantt chart genetic algorithms Geoffrion's method given by equation goal programming ideal point IMC-DSS important interactive interface ISTM method iteration judgements linear programming machine MADM problem Marginal Utility Function MCDM MCGA minimax minimising minimum set MODM methods multiobjective multiple criteria decision nonlinear normalized objective function obtained operating optimal solution optimisation pairwise comparisons Pareto optimal Pareto surface performance population preference information quasi-Newton methods ranking relative weights represented requirements scenarios selection ship design shown in Figure shown in Table space Step String techniques TOPSIS method trade-off UTA method Value System weight assignment weight vector y₁ αι аз