2014•Unpublished venueRequires access

Non-dominated sorting differential evolution with improved directional convergence and spread for multiobjective optimization

Wentao Guo, Xinjie Yu

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Abstract

A non-dominated sorting differential evolution algorithm with improved directional convergence and spread (NSDE-IDCS) is developed. Taking advantage of differential evolution, searching direction for a dominated solution is determined by its nearest non-dominated neighbor, while searching direction for a non-dominated solution is determined by other two non-dominated solutions. A simplex local search operator with an adaptive search probability is embedded to further exploit the neighborhood of non-dominated solutions.

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What this paper is about

A non-dominated sorting differential evolution algorithm with improved directional convergence and spread (NSDE-IDCS) is developed. Taking advantage of differential evolution, searching direction for a dominated solution is determined by its nearest non-dominated neighbor, while searching direction for a non-dominated solution is determined by other two non-dominated solutions. A simplex local search operator with an adaptive search probability is embedded to further exploit the neighborhood of non-dominated solutions.

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Available abstract

A non-dominated sorting differential evolution algorithm with improved directional convergence and spread (NSDE-IDCS) is developed. Taking advantage of differential evolution, searching direction for a dominated solution is determined by its nearest non-dominated neighbor, while searching direction for a non-dominated solution is determined by other two non-dominated solutions. A simplex local search operator with an adaptive search probability is embedded to further exploit the neighborhood of non-dominated solutions.

Key concepts: Sorting, Differential evolution, Convergence (economics), Exploit, Mathematical optimization, Simplex, Computer science, Differential (mechanical device)

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