| Results given in Ref. [23] | Results given by hybrid genetic algorithm | |||||
Objective | Stage | Reliability | Component | Simulation result | Reliability | Component | Simulation result |
Maximize System Reliability | 1 2 3 4 | 0.866288 0.850029 0.918417 0.913049 | 6.0 6.0 4.0 4.0 | Rs = 0.999881 Cs = 381.12183 Ws = 485.77850 Vs = 188.0 | 0.8971 0.8659 0.9358 0.8769 | 5 6 4 5 | Rs = 0.9999 Cs = 381.5582 Ws = 475.1981 Vs = 195 |
Minimize System Cost | 1 2 3 4 | 0.559777 0.599392 0.685273 0.703375 | 6.0 6.0 4.0 4.0 | Rs = 0.971340 Cs = 54.472889 Ws = 485.778504 Vs = 188.0 | 0.7997 0.7896 0.7154 0.8393 | 4 4 5 4 | Rs = 0.9939 Cs = 133.4582 Ws = 346.2031 Vs = 155 |
Minimize System Weight | 1 2 3 4 | 0.864883 0.944821 0.905934 0.880399 | 3.0 2.0 2.0 2.0 | Rs = 0.971597 Cs = 295.029388 Ws = 107.352295 Vs = 370 | 0.9668 0.8715 0.9572 0.9382 | 2 2 2 2 | Rs = 0.9769 Cs = 440.5520 Ws = 89.0309 Vs = 32 |
Multi- Objective Optimization | 1 2 3 4 | 0.820009 0.806433 0.869349 0.865680 | 4.0 3.0 3.0 2.0 | Rs = 0.971641 Cs = 119.04067 Ws = 177.234863 Vs = 69.0 | 0.8536 0.7977 0.9189 0.8133 | 3 3 2 3 | Rs = 0.9757 Cs = 114.0175 Ws = 147.0485 Vs = 57 |