Research Article

Multiobjective Parallel Chaos Optimization Algorithm with Crossover and Merging Operation

Table 2

Comparison results of PCOA and other MOAs based on the generational distance.

PCOANSGA-IISPEA2MOPSO
FunctionMeanSDMeanSDMeanSDMeanSD

Schaffer2.3407e − 32.9498e − 42.1572e − 32.0999e − 42.1232e − 32.1130e − 42.9285e − 21.5566e − 2
Kursawe3.1164e − 33.7829e − 42.8974e − 32.3637e − 47.1576e − 11.2523e − 23.0147e − 21.7442e − 3
Fonseca2.1940e − 33.8326e − 42.5656e − 32.0082e − 41.8573e − 31.0731e − 42.1416e − 27.4183e − 3
ConstrEx4.9281e − 37.3116e − 45.1349e − 32.4753e − 44.8247e − 33.7650e − 44.5437e − 36.8558e − 4
Srinivas2.5572e − 34.9703e − 43.7069e − 35.1034e − 42.1059e − 34.7502e − 42.7623e − 32.0794e − 4
Tanaka3.7950e − 31.0075e − 34.0488e − 34.3465e − 43.8175e − 34.9142e − 45.0877e − 34.5564e − 4
ZDT11.3367e − 14.2378e − 21.3437e − 31.4078e − 48.6104e − 32.5973e − 31.8564e − 17.7429e − 2
ZDT22.0960e − 15.4732e − 29.8112e − 46.4138e − 42.4766e − 21.6083e − 25.2428e − 12.9699e − 1
ZDT32.8144e − 13.5513e − 22.4783e − 31.2746e − 49.7165e − 35.2305e − 34.3418e − 16.4880e − 2
ZDT46.5237e − 24.2511e − 35.1635e − 21.3281e − 39.2512e − 14.2821e − 1
ZDT67.3128e − 26.5390e − 37.5818e − 26.0797e − 31.9309e − 21.3994e − 35.2135e − 22.4963e − 2