Dynamic Programming and Taguchi Method Optimization of Water-Treatment-Plant Design
System and process optimization are both necessary for overall system design in system optimization models, the objective is to determine the optimal system configuration while assuming the design and operating parameters of each individual process. In process optimization models the objective is to find the design and operating parameters of individual processes. The major disadvantages of GP and NLP algorithms are that global optima is not assured and they can not be directly used for system optimization because of the presence of discrete decision variables and required high computer storage [Dharmappa 1994] [Desmond F. Lawler. 2005] Using DP solely for large problems requires very high computer time for Data Processing [Mhiaisalkar 1993]. The model of this research is DP model that employs Taguchi Experimental Design Method, whereupon the time of model analysis has reduced considerably. . Case study showed the capability of model in savings of roughly 9.5% in capital and annualized costs, compared to the conventional design besides the software has capability to performing sensitivity analysis and showing interactions between various Decision variables.
