Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization
Brunel University of London · De Montfort University
Abstract
It is commonly accepted that Pareto-based evolutionary multiobjective optimization (EMO) algorithms encounter difficulties in dealing with many-objective problems. In these algorithms, the ineffectiveness of the Pareto dominance relation for a high-dimensional space leads diversity maintenance mechanisms to play the leading role during the evolutionary process, while the preference of diversity maintenance mechanisms for individuals in sparse regions results in the final solutions distributed widely over the objective space but distant from the desired Pareto front. Intuitively, there are two ways to address this problem: 1) modifying the Pareto dominance relation and 2) modifying the diversity maintenance…
Citation impact
- FWCI
- 23.83
- Percentile
- 100%
- References
- 104
Authors
3Topics & keywords
- Algorithm
- Computer science
- Multi-objective optimization
- Pareto principle
- Mathematical optimization
- Estimation
- Mathematics
- Engineering