Self-adaptive combination of global tabu search and local search for nonlinear equations
Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization p...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | article |
| Language: | eng |
| Published: |
2014
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10400.22/4067 |
| Country: | Portugal |
| Oai: | oai:recipp.ipp.pt:10400.22/4067 |
| Summary: | Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods. |
|---|