A tabu search meta-heuristic approach to the dual response systems problem

This paper presents an alternative approach to the dual response systems problem by utilizing a tabu search algorithm that yields a string of solutions and examine the trade-offs graphically and systematically how the controllable variables simultaneously impact the mean and the standard deviation of a characteristic of interest relevant to an industrial process. Heuristic-based search techniques may be very useful for cases where interactive multi-objective optimization techniques are not available due to lack of willingness of decision-makers. A further advantage of tabu search is its simplicity and we show that the entire process only occupies a few lines of codes and generates string of solutions in speedy manner especially for the larger-the-better/smaller-the-better cases of Taguchi’s robust parameter design. The procedure is illustrated with an example.