Now showing items 1-4 of 4
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 ...
Evolutionary dynamic constrained optimization: Test suite construction and algorithm comparisons
Many real-world applications can be modelled as dynamic constrained optimization problems (DCOPs). Due to the fact that objective function and/or constraints change over time, solving DCOPs is a challenging task. Although ...
AREA: An adaptive reference-set based evolutionary algorithm for multiobjective optimisation
Population-based evolutionary algorithms have great potential to handle multiobjective optimisation problems. However, the performance of these algorithms depends largely on problem characteristics. There is a need to ...
A scalable test suite for dynamic multiobjective optimization
Dynamic multiobjective optimization (DMO) has gained increasing attention in recent years. Test problems are of great importance in order to facilitate the development of advanced algorithms that can handle dynamic ...