Now showing items 1-3 of 3
A Pareto-based evolutionary algorithm using decomposition and truncation for dynamic multi-objective optimization
Maintaining a balance between convergence and diversity of the population in the objective space has been widely recognized as the main challenge when solving problems with two or more conflicting objectives. This is added ...
Novel prediction strategies for dynamic multi-objective optimization
(IEEE Press, 2019-06-13)
This paper proposes a new prediction-based dynamic multi-objective optimization (PBDMO) method, which combines a new prediction-based reaction mechanism and a popular regularity model-based multi-objective estimation of ...
Solving dynamic multi-objective problems with an evolutionary multi-directional search approach
The challenge of solving dynamic multi-objective optimization problems is to effectively and efficiently trace the varying Pareto optimal front and/or Pareto optimal set. To this end, this paper proposes a multi-direction ...