Name
Abstract | ||
|---|---|---|
We introduce a novel global optimization method called Continuous GRASP (C-GRASP) which extends Feo and Resende's greedy randomized adaptive search proce- dure (GRASP) from the domain of discrete optimization to that of continuous global opti- mization. This stochastic local search method is simple to implement, is widely applicable, and does not make use of derivative information, thus making it a well-suited approach for solving global optimization problems. We illustrate the effectiveness of the procedure on a set of standard test problems as well as two hard global optimization problems. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/s11590-006-0021-6 | Optimization Letters |
Keywords | Field | DocType |
. grasp,sto- chastic local search,stochastic algorithm,global optimization,nonlinear programming.,continuous optimization,nonlinear programming,discrete optimization,local search | Continuous optimization,Derivative-free optimization,Mathematical optimization,Global optimization,Discrete optimization,Random optimization,Engineering optimization,Optimization problem,Mathematics,Metaheuristic | Journal |
Volume | Issue | ISSN |
1 | 2 | 1862-4472 |
Citations | PageRank | References |
40 | 2.44 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. J. Hirsch | 1 | 61 | 3.50 |
| Cláudio Nogueira de Meneses | 2 | 52 | 3.67 |
| Panos M. Pardalos | 3 | 141 | 19.60 |
| Mauricio G. C. Resende | 4 | 3729 | 336.98 |