A Novel Selection Approach for Genetic Algorithms for Global Optimization of Multimodal Continuous Functions

Table 2

Detail of benchmark functions for comparison.

Benchmark	Fitness function	Search limits	Optimum value	Properties
Axis parallel ellipsoid		[−5.12, 5.12]	0	Continues, convex, unimodal
Beale		[−4.5, 4.5]	0	Multimodal, nonseparable
Continues
Bohachevsky		[−100, 100]	0	Multimodal, nonseparable
Colville		[−10, 10]	0	Unimodal, nonseparable
Drop-wave		[−5.12, 5.12]	−1	Multimodal, nonseparable
Egg-holder		[−5.12, 5.12]	−959.6407	Nonconvex, multimodal
Ellipsoidal		[−n, n]	0	Unimodal
Rosenbrock		[−2.048, 2.048]	0	Unimodal, nonseparable
Schaffer		[−100, 100]	0	Unimodal, nonseparable
Schwefel	)	[−500, 500]	0	Multimodal, nonseparable