Before improving the differential evolution (DE), the premature convergence feature of the differential evolution must be analyzed, which demonstrates that the differential evolution is not able to ...

Differential Evolution (DE) is a straightforward yet powerful method for numerical optimization. The performance of the DE algorithm is greatly affected by its parameter configuration, as a result, a ...

To tackle the planning and optimization difficulties for large-scale observation tasks, we propose an improved Differential Evolution (DE) algorithm incorporating a Hybrid Initialization strategy to ...

These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search ...