- Author:
- Sunil Umakant Mohandas,
- Supervisors:
- Thomas A. Phelps,
- Kenneth M. Ragsdell
The process of decision-making invariably involves choosing viable but conflicting decision alternatives in a fuzzy environment. A fuzzy goal programming methodology is investigated to treat such a multi-criterion decision-making problem. The theory of fuzzy sets is used to aggregate conflicting objectives of a multi-criterion decision-making problem by constructing a representative decision function as a fuzzy set. Theorems which guarantee an optimal or pareto-optimal solution are stated and proved. Two optimization algorithms are presented which to find an optimum solution to the fuzzy decision function. The fuzzy goal programming methodology is demonstrated by using examples from the areas of structural optimization and mechanical design. The algorithms presented in this work will be useful in solving any multi-objective decision-making problem where non-stochastic uncertainty hovers in the description of the problem.
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