Abstract
In this paper, a hybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, is proposed. The simulated annealing algorithm is used to locate descent points for previously converged local minima. The combined method has the descent property and the convergence is monotonic. To demonstrate the effectiveness of the proposed hybrid descent method, several multi-dimensional non-convex optimization problems are solved. Numerical examples show that global minimum can be sought via this hybrid descent method.
| Original language | English |
|---|---|
| Pages (from-to) | 229-238 |
| Number of pages | 10 |
| Journal | Journal of Global Optimization |
| Volume | 28 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Feb 2004 |
Keywords
- Descent method
- Global minimum
- Simulating annealing
ASJC Scopus subject areas
- Computer Science Applications
- Control and Optimization
- Management Science and Operations Research
- Applied Mathematics