Refine
Year of publication
Document Type
- Conference Proceeding (17)
- Article (8)
- Part of a Book (3)
- Doctoral Thesis (1)
- Other (1)
Institute
Is part of the Bibliography
- yes (30)
Keywords
- Constrained Optimization (3)
- evolution strategies (3)
- ESG (2)
- Evolution Strategies (2)
- Sustainable Smart Service (2)
- Value co-creation (2)
- meta-es (2)
- mutation strength (2)
- Application (1)
- Automobilindustrie (1)
A modified matrix adaptation evolution strategy with restarts for constrained real-world problems
(2020)
In combination with successful constraint handling techniques, a Matrix Adaptation Evolution Strategy (MA-ES) variant (the εMAg-ES) turned out to be a competitive algorithm on the constrained optimization problems proposed for the CEC 2018 competition on constrained single objective real-parameter optimization. A subsequent analysis points to additional potential in terms of robustness and solution quality. The consideration of a restart scheme and adjustments in the constraint handling techniques put this into effect and simplify the configuration. The resulting BP-εMAg-ES algorithm is applied to the constrained problems proposed for the IEEE CEC 2020 competition on Real-World Single-Objective Constrained optimization. The novel MA-ES variant realizes improvements over the original εMAg-ES in terms of feasibility and effectiveness on many of the real-world benchmarks. The BP-εMAg-ES realizes a feasibility rate of 100% on 44 out of 57 real-world problems and improves the best-known solution in 5 cases.
