mlsanityData to 14 Oct 2026

Parameterized Analysis of Multi-objective Evolutionary Algorithms and the Weighted Vertex Cover Problem

arXiv 1604.01495 ↗First posted 6 Apr 2016cs.NE cs.DScited by 1

Not on the map. Why?

Abstract (arXiv)

A rigorous runtime analysis of evolutionary multi-objective optimization for the classical vertex cover problem in the context of parameterized complexity analysis has been presented by Kratsch and Neumann (2013). In this paper, we extend the analysis to the weighted vertex cover problem and provide a fixed parameter evolutionary algorithm with respect to OPT, the cost of the the optimal solution for the problem. Moreover, using a diversity mechanisms, we present a multi-objective evolutionary algorithm that finds a 2-approximation in expected polynomial time and introduce a population-based evolutionary algorithm which finds a (1+varepsilon)-approximation in expected time O(n· 2^min n,2(1- varepsilon)OPT + n3).

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 6 Apr 2016.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2022: 1.

1 paper.