A Multiobjective Genetic Algorithm for the Localization of Optimal and Nearly Optimal Solutions Which Are Potentially Useful: nevMOGA

Table 2

Analysis of a MOP example with four objectives (, , , and ) and four possible solutions ( to ) where the MOP is reduced by aggregating and () and and ().

Solutions
[0 0]	0.2	0.2	0.4	0.2	0.2	0.4
[0 1]	0.18	0.22	0.4	0.24	0.16	0.4
[1 0]	0.179	0.221	0.4	0.241	0.161	0.402
[1 1]	0.9	0.199	1.119	0.9	0.9	1.8