Dual Response Surface Optimization using Multiple Objective Genetic Algorithms
다목적 유전 알고리즘을 이용한 쌍대반응표면최적화

Dong-Hee Lee, Bo-Ra Kim, Jin-Kyung Yang, Seon-Hye Oh
2017 Journal of Korean Institute of Industrial Engineers  
Dual response surface optimization (DRSO) attempts to optimize mean and variability of a process response variable using a response surface methodology. In general, mean and variability of the response variable are often in conflict. In such a case, the process engineer need to understand the tradeoffs between the mean and variability in order to obtain a satisfactory solution. Recently, a Posterior preference articulation approach to DRSO (P-DRSO) has been proposed. P-DRSO generates a number
more » ... non-dominated solutions and allows the process engineer to select the most preferred solution. By observing the non-dominated solutions, the DM can explore and better understand the trade-offs between the mean and variability. However, the non-dominated solutions generated by the existing P-DRSO is often incomprehensive and unevenly distributed which limits the practicability of the method. In this regard, we propose a modified P-DRSO using multiple objective genetic algorithms. The proposed method has an advantage in that it generates comprehensive and evenly distributed non-dominated solutions. †
doi:10.7232/jkiie.2017.43.3.164 fatcat:peseja5qpbfvjpxaja4ywccxxi