Antioptimisation of Trusses Using Two-Level Population-Based Incremental Learning

Table 1

Optimum results of AOP1.

MHs	HybridGA		PBILb5		PBILw5		PBILw5m		PBILw1		PBILw10
	Avrg	Stdev	Avrg	Stdev	Avrg	Stdev	Avrg	Stdev	Avrg	Stdev	Avrg	Stdev
𝑥1	0.5048	0.0242	0.5613	0.1011	0.6247	0.1176	0.6333	0.1587	0.6344	0.1558	0.5914	0.1302
𝑥2	0.0029	0.0001	0.0038	0.0003	0.0037	0.0004	0.0038	0.0005	0.0038	0.0004	0.0038	0.0004
𝑦1	200.0000	0.0000	399.1398	130.0818	370.3226	142.7784	400.8602	164.3949	405.1613	157.4620	424.0860	151.7861
𝑓(𝐱,𝐲)	49.9355	1.6789	67.2216	4.8174	68.2111	5.5543	70.2185	5.9409	69.9382	4.6033	69.4287	5.3346
max𝑔𝑖	−0.0018	0.0024	−0.0050	0.0000	−0.0050	0.0000	−0.0050	0.0000	−0.0050	0.0000	−0.0050	0.0000