Abstract
The data and behavior of many engineering systems are not known precisely and the designer is required to design the system in the presence of fuzziness in the goals, constraints and consequences of possible actions. Two broad approaches, known as the α-cut approach and the λ-formulation, are applicable for the optimum design of fuzzy engineering systems. These two approaches are presented in the context of multiobjective optimization of fuzzy engineering systems. The performance characteristics of the methods are studied comparatively with the help of two structural multiobjective design problems. The first problem involves the design of a three-bar truss for minimum weight and minimum deflection. The second problem deals with the design of a 25-bar truss for minimum weight, minimum deflection and maximum fundamental natural frequency of vibration. The results indicate that the α-cut approach provides the results in a parametric form while the λ-formulation yields an overall compromise solution to the design problem.
