Solving Constrained Global Optimization Problems by Using Hybrid Evolutionary Computing and Artificial Life Approaches

Table 6

The best parameter settings of the best solution obtained using the AIA-PSO algorithm from TPs 1–13.

TP number	𝜒	𝑐1	𝑐2	𝜌	𝑝𝑚,PSO
1	0.44896780	0.71709211	1.93302154	72140307110	0.4058
2	1	1.36225259	1.97905466	182831007	0.5
3	0.46599492	0.90346435	1.89697456	69125199709	0.2613
4	0.98124982	0.27882671	0.87437226	85199047430	0.1
5	0.99082484	0.1	1.11371788	4231387044	0.5
6	0.82869043	0.88773247	2	1387448505	0.5
7	0.87571243	1.89936723	0.74306310	94752095153	0.2194
8	0.93583844	1.53906226	1.30374874	22520728225	0.1798
9	1	0.22556712	1.52263349	67578847151	0.4507
10	1	1.93003999	0.1	1351461763	0.5
11	1	1.51209364	1.63826995	1811017789	0.5
12	0.52068067	0.1	2	81914376144	0.1
13	0.82395890	1.60107152	0.93611204	17767111886	0.1813