Abstract
A formulation for multiobjective optimization for engineering design based on fuzzy sets is presented. Models for the optimization problem and operations to introduce model variations are described formally. Under a reasonable set of rules it is shown that solutions to fuzzy multiobjective problems are weakly efficient and can reproduce solutions obtained by traditional methods such as compromise and goal programming. Results are easily implemented in computations.

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