Improved Quick Hypervolume Algorithm

12/11/2016
by   Andrzej Jaszkiewicz, et al.
0

In this paper, we present a significant improvement of Quick Hypervolume algorithm, one of the state-of-the-art algorithms for calculating exact hypervolume of the space dominated by a set of d-dimensional points. This value is often used as a quality indicator in multiobjective evolutionary algorithms and other multiobjective metaheuristics and the efficiency of calculating this indicator is of crucial importance especially in the case of large sets or many dimensional objective spaces. We use a similar divide and conquer scheme as in the original Quick Hypervolume algorithm, but in our algorithm we split the problem into smaller sub-problems in a different way. Through both theoretical analysis and computational study we show that our approach improves computational complexity of the algorithm and practical running times.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/19/2012

Quick HyperVolume

We present a new algorithm to calculate exact hypervolumes. Given a set ...
research
12/21/2020

Analyzing Dominance Move (MIP-DoM) Indicator for Multi- and Many-objective Optimization

Dominance move (DoM) is a binary quality indicator that can be used in m...
research
09/17/2018

Merge Non-Dominated Sorting Algorithm for Many-Objective Optimization

Many Pareto-based multi-objective evolutionary algorithms require to ran...
research
04/15/2020

Improving Many-objective Evolutionary Algorithms by Means of Expanded Cone Orders

Given a point in m-dimensional objective space, the local environment of...
research
12/18/2018

Fast Exact Computation of Expected HyperVolume Improvement

In multi-objective Bayesian optimization and surrogate-based evolutionar...
research
04/18/2019

Uncrowded Hypervolume Improvement: COMO-CMA-ES and the Sofomore framework

We present a framework to build a multiobjective algorithm from single-o...
research
11/08/2022

The Hypervolume Indicator Hessian Matrix: Analytical Expression, Computational Time Complexity, and Sparsity

The problem of approximating the Pareto front of a multiobjective optimi...

Please sign up or login with your details

Forgot password? Click here to reset