(2011-6286) A novel method for multi-objective design optimization based on fuzzy systems

Abstract

A novel strategy to design optimization is expressedusing the fuzzy preference function concept. This method efficientlyuses the designer's experiences by preference functions and it isalso able to transform a constrained multi-objective optimizationproblem into an unconstrained single-objective optimization problem.These two issues are the most important features of the proposedmethod which using them, you can achieve a more practical solutionin less time. To implement the proposed method, two designoptimizations of an unmanned aerial vehicle are considered whichare: deterministic and non-deterministic optimizations. Theoptimization problem in this paper is a constrained multi-objectiveproblem that with attention to the ability of genetic algorithm,this algorithm is selected as the optimizer. Uncertainties areconsidered and the Monte Carlo simulation (MCS) method is used foruncertainties modeling. The obtained results show a good performanceof this technique in achieving optimal and robust solutions.