A robust posterior preference decision-making approach to multiple response process design

Setting of process variables to meet required specification of quality characteristics is one of the important problems in quality control processes. In general, most industrial and production systems are dealing with several different responses and the problem is to simultaneously optimise these responses. To obtain the most satisfactory solution, a decision-makers (DM) preference on the trade-offs among the quality characteristics should be incorporated into the optimisation procedure. This study suggests a robust posterior preference articulation approach based on a non-dominated sorting genetic algorithm (NSGA-II) to optimise multiple responses. In order to minimise the variation in deviation of responses from targets, maximum and sum of deviations are taken into consideration. To investigate the performance of the suggested approach, a computational analysis on a real world chemical engineering example is performed. Results show the superiority of the proposed approach compared to the existing techniques.