Quick HyperVolume
Lu\'is M. S. Russo, Alexandre P. Francisco
TL;DR
The paper introduces 'Quick Hypervolume', an algorithm that efficiently computes exact hypervolumes in multi-dimensional spaces, with strong theoretical foundations and competitive experimental performance.
Contribution
It provides a new algorithm with proven theoretical advantages and practical efficiency for calculating hypervolumes in multiobjective optimization.
Findings
Theoretical analysis shows significant improvements over existing methods.
Experimental results demonstrate competitive performance.
The algorithm is suitable for integration into multiobjective evolutionary algorithms.
Abstract
We present a new algorithm to calculate exact hypervolumes. Given a set of -dimensional points, it computes the hypervolume of the dominated space. Determining this value is an important subroutine of Multiobjective Evolutionary Algorithms (MOEAs). We analyze the "Quick Hypervolume" (QHV) algorithm theoretically and experimentally. The theoretical results are a significant contribution to the current state of the art. Moreover the experimental performance is also very competitive, compared with existing exact hypervolume algorithms. A full description of the algorithm is currently submitted to IEEE Transactions on Evolutionary Computation.
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Taxonomy
TopicsAdvanced Multi-Objective Optimization Algorithms · Evolutionary Algorithms and Applications · Metaheuristic Optimization Algorithms Research