2020/02/25 by Claudio Lucio do Val Lopes, Lopes, Claudio Lucio do Val, Flávio Vinícius Cruzeiro Martins +3
Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE) #cs.NE
paper · pdf · doi:10.48550/arxiv.2002.10842
arXiv admin note: text overlap with arXiv:2001.03657
openalex publication_date 2020/02/25 · arxiv created 2020/05/14 · arxiv updated 2020/05/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Dominance move (DoM) is a binary quality indicator to compare solution sets in multiobjective optimization. The indicator allows a more natural and intuitive relation when comparing solution sets. It is Pareto compliant and does not demand any parameters or reference sets. In spite of its advantages, the combinatorial calculation nature is a limitation. The original formulation presents an efficient method to calculate it in a biobjective case only. This work presents an assignment formulation to calculate DoM in problems with three objectives or more. Some initial experiments, in the biobjective space, were done to present the model correctness. Next, other experiments, using three dimensions, were also done to show how DoM could be compared with other indicators: inverted generational distance (IGD) and hypervolume (HV). Results show the assignment formulation for DoM is valid for more than three objectives. However, there are some strengths and weaknesses, which are discussed and detailed. Some notes, considerations, and future research paths conclude this work.