Applying a New Adaptive Genetic Algorithm to Study the Layout of Drilling Equipment in Semisubmersible Drilling Platforms

Table 3

Simulation results of different algorithms for .

Algorithm	Stats	(1.0)	(0.0)	(0.0)	(−78.332314)	(0.0)
PSO	Best	1.0	0.0	0.0
	Mean	0.999984	0.11968	0.003795		1.798256
	Std.
CMAES	Best	0.999925	0.029721	0.0		0.0
	Mean	0.996273	0.070160	0.001008		0.254623
	Std.
SaDE1	Best	0.999998	0.000527	0.0
	Mean	0.997836	0.045876	0.002766		0.387544
	Std.
SaDE2	Best	1.0	0.000561	0.0
	Mean	0999328	0.001673	0.007731		0.913510
	Std.
T-AAGA	Best	1.0	0.0	0.0	−78.332306	0.0
	Mean	0.999973	0.007468	5.22E  − 05	−77.453346	0.118650
	Std.	4.05E  − 06	1.44E  − 04	6.05E  −  05	2.36E  − 00	2.03E  − 02