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Article

Improved sampling of the pareto-front in multiobjective genetic optimizations by steady-state evolution: a pareto converging genetic algorithm.

Evolutionary computation - 1 Jan 2002

Kumar Rajeev, Rockett Peter

Abstract excerpt

Previous work on multiobjective genetic algorithms has been focused on preventing genetic drift and the issue of convergence has been given little attention. In this paper, we present a simple steady-state strategy, Pareto Converging Genetic Algorithm (PCGA), which naturally samples the solution space and ensures population advancement towards the Pareto-front. PCGA eliminates the need for sharing/niching and...

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PMID: 12227997
DOI: 10.1162/106365602760234117

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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