Fast hypervolume approximation scheme based on a segmentation strategy

DOI10.1016/j.ins.2019.02.054zbMath1456.90151OpenAlexW2917481402MaRDI QIDQ1999059

Lei Chen, Weisen Tang, Kay Chen Tan, Yiu-ming Cheung, Hai-Lin Liu

Publication date: 18 March 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2019.02.054

zbMATH Keywords

hypervolumeMonte Carlo simulationevolutionary algorithmmany-objective optimization

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (1)

Design and analysis of helper-problem-assisted evolutionary algorithm for constrained multiobjective optimization

Uses Software

• MOEA/D
• jMetal
• SMS-EMOA
• HypE
• weightedHypervolume

Cites Work

• Unnamed Item
• SMS-EMOA: multiobjective selection based on dominated hypervolume
• A box decomposition algorithm to compute the hypervolume indicator
• Faster Hypervolume-Based Search Using Monte Carlo Sampling
• Approximating the Volume of Unions and Intersections of High-Dimensional Geometric Objects

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