Dominance Move: A Measure of Comparing Solution Sets in Multiobjective Optimization
Miqing Li, Xin Yao

TL;DR
This paper introduces the dominance move (DoM), a new measure for comparing solution sets in multiobjective optimization that does not require problem-specific information and effectively captures solution quality differences.
Contribution
The paper proposes the dominance move (DoM) measure, an exact and efficient method to compare solution sets without needing additional problem knowledge or parameters.
Findings
DoM accurately reflects differences between solution sets.
An efficient recursive algorithm for biobjective cases is developed.
DoM outperforms existing quality measures in tests.
Abstract
One of the most common approaches for multiobjective optimization is to generate a solution set that well approximates the whole Pareto-optimal frontier to facilitate the later decision-making process. However, how to evaluate and compare the quality of different solution sets remains challenging. Existing measures typically require additional problem knowledge and information, such as a reference point or a substituted set of the Pareto-optimal frontier. In this paper, we propose a quality measure, called dominance move (DoM), to compare solution sets generated by multiobjective optimizers. Given two solution sets, DoM measures the minimum sum of move distances for one set to weakly Pareto dominate the other set. DoM can be seen as a natural reflection of the difference between two solutions, capturing all aspects of solution sets' quality, being compliant with Pareto dominance, and…
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Taxonomy
TopicsAdvanced Multi-Objective Optimization Algorithms · Optimal Experimental Design Methods · Metaheuristic Optimization Algorithms Research
