Harmonic Average Distant Metric for MMOPs
Talking about distance metrics in our last post, today we present the Harmonic Average Distance (HAD) metric which we use to deal with multi-modal multi-objective optimization Problems (MMOPs). One major challenge in MMOPs is that we need to measure the distances between the solutions in the decision space with large dimensionalities while considering the qualities in the objective space. The example below shows a 2D decision variable space. While the traditional crowding distance metric gives a higher priority to C than E, the HAD metric does the vice versa and E gets selected.
More information can be found in our recently accepted paper which we will present at EMO 2021:
- Mahrokh Javadi and Sanaz Mostaghim
- A Neighborhood-based Density Measure for Multimodal Multi-Objective Optimization
- Accepted at the 11th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2021), Shenzhen, China, 2021