Name
Abstract | ||
|---|---|---|
Continuous GRASP (C-GRASP) is a stochastic local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints (Hirsch et al., 2007). Like a greedy randomized adaptive search procedure (GRASP), a C-GRASP is a multi-start procedure where a starting solution for local improvement is constructed in a greedy randomized fashion. In this paper, we describe several improvements that speed up the original C-GRASP and make it more robust. We compare the new C-GRASP with the original version as well as with other algorithms from the recent literature on a set of benchmark multimodal test functions whose global minima are known. Hart’s sequential stopping rule (1998) is implemented and C-GRASP is shown to converge on all test problems. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.ejor.2010.02.009 | European Journal of Operational Research |
Keywords | Field | DocType |
GRASP,Continuous GRASP,Global optimization,Multimodal functions,Continuous optimization,Heuristic,Stochastic algorithm,Stochastic local search,Nonlinear programming | Continuous optimization,Mathematical optimization,GRASP,Global optimization,Algorithm,Greedy algorithm,Local search (optimization),Greedy randomized adaptive search procedure,Stochastic programming,Mathematics,Metaheuristic | Journal |
Volume | Issue | ISSN |
205 | 3 | 0377-2217 |
Citations | PageRank | References |
21 | 1.06 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. J. Hirsch | 1 | 61 | 3.50 |
| Panos M. Pardalos | 2 | 3720 | 397.84 |
| Mauricio G. C. Resende | 3 | 3729 | 336.98 |