Well-distributed Pareto front by using the ∉-MOGA evolutionary algorithm
作者： X. Blasco , M. Martínez , J. M. Herrero , J. Sanchis
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摘要: In the field of multiobjective optimization, important efforts have been made in recent years to generate global Pareto fronts uniformly distributed. A new evolutionary algorithm, called ∉-MOGA, has designed converge towards ΘP*, a reduced but well distributed representation set ΘP. The algorithm achieves good convergence and distribution front J(ΘP) with bounded memory requirements which are established one its parameters. Finally, optimization problem three-bar truss is presented illustrate performance.
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