Multiobjective Optimization Dealing With Uncertainty
Sunil U. Mohandas, Eric P. Sandgren · 1989
Abstract An algorithm to handle uncertainty in a multiobjective design optimization problem is developed. The procedure is applied to three examples where objective functions in each of them compete against each other. The uncertainty in the description of objective functions is modeled by using fuzzy goals and the terms of natural language. Multiobjective function is formulated as a fuzzy set. The minimization is carried out using a combination of the Complex Box method and a technique of ranking of fuzzy sets.