A Multiobjective Optimization Approach via Systematical Modification of the Desirability Function Shapes

ALTINÖZ Ö. T., OZANSOY A., Ciuprina G.

8th International Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, Romania, 23 - 25 May 2013 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/atee.2013.6563481
  • City: Bucharest
  • Country: Romania
  • Keywords: multiobjective optimization, desirability function, benchmark functions
  • TED University Affiliated: Yes


In this study, a method for solution of the multi-objective optimization problems via the desirability function aided particle swarm optimization has been proposed. The desirability function has been applied for normalization of each objective and then aggregation to a single objective. The geometric mean of the desirability values regarding each objective has been calculated as a part of the method. On the other hand, using a single-objective optimization algorithm yields a single solution rather than a complete solution set. Hence, the idea of changing the shapes of the desirability functions is implemented in order to achieve a complete solution set; in fact, this constitutes the main theme of this study. Therefore, the multi-objective problem has been degraded to a single-objective one, and it has been solved numerous times for each alternative desirability function shape. As a result, a set of biased solutions has been obtained in a very practical manner.