In this study, these parameters are selected as objective functions in the multi-objective optimization framework.
Fiscal year 2010 was selected as objective year and 2005 as basic year.
One output is selected as objective to be minimized, while other outputs must satisfy given threshold values.
RMSE is selected as objective measure of motion reliability, comparing the estimated motion with the observed motion.
In addition, the mutual information and the total mean square error criteria were selected as objective functions [15, 16].
Annual benefit is selected as objective function which shows the benefit of CCHP-ORC system compared with conventional system.
Finally, multi-objective optimization for different FGT are carried out, while specified energy absorption and peak force are selected as objective functions.
For example, the mutual information and the total mean square error (MSE) criteria are selected as objective functions in [7, 8], respectively.
The thrust coefficient CT and lift coefficient CN are selected as objective functions, and the sampling points are obtained numerically by using a Latin hypercube design method.
Total cost of the system (the capital and operating costs) is selected as objective function and Genetic Algorithm is applied to find the minimum of it for each case.
