Research Article

5D Parameter Estimation of Near-Field Sources Using Hybrid Evolutionary Computational Techniques

Table 1

Parameter setting for GA, PS, and IPA.

GAPS IPA
ParametersSettingsParametersSettingParametersSetting

Population size240Starting pointBest chromosome achieved by GAStarting pointBest chromosome achieved by GA

Number of generations1000Polling orderConsecutiveSubproblem algorithmIdl factorization

Migration directionBoth waysMaximum iteration1000Maximum perturbation0.1

Crossover fraction0.2Function evaluation17000Minimum perturbation

CrossoverHeuristicMesh size 01ScalingObjective and constraint

Function tolerance10–12Expansion factor2.0HessianBFGS

Initial range(0-1)Contraction factor0.5Derivative typeCentral difference

Scaling functionRankPenalty factor100Penalty factor100

SelectionStochastic uniformBind tolerance10-04Maximum function evaluation50000

Elite count2Mesh tolerance 10-07Maximum iteration1000

Mutation functionAdaptive feasibleX tolerance10-06X tolerance10–12