Name
Abstract | ||
|---|---|---|
We present a new method for finding a global optimal solution to a discrete stochastic optimization problem. This method resembles the simulated annealing method for discrete deterministic optimization. However, in our method the annealing schedule (the cooling temperature) is kept fixed, and the mechanism for estimating the optimal solution is different from that used in the original simulated annealing method. We state a convergence result that shows that our method converges almost surely to a global optimal solution under mild conditions. We also present empirical results that illustrate the performance of the proposed approach on a simple example. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1145/224401.224468 | Winter Simulation Conference |
Keywords | Field | DocType |
new search algorithm,discrete deterministic optimization,optimal solution,simulated annealing method,present empirical result,discrete stochastic optimization problem,original simulated annealing method,new method,convergence result,annealing schedule,global optimal solution,stochastic optimization,discrete event simulation,global optimization,search algorithm,simulated annealing,temperature,stochastic processes,approximation algorithms,algorithm design and analysis | Simulated annealing,Hill climbing,Mathematical optimization,Stochastic optimization,Discrete optimization,Computer science,Adaptive simulated annealing,Combinatorial optimization,Local search (optimization),Metaheuristic | Conference |
ISBN | Citations | PageRank |
0-7803-3018-8 | 6 | 1.33 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mahmoud H. Alrefaei | 1 | 90 | 10.14 |
| Sigrún Andradóttir | 2 | 548 | 55.09 |