Name
Title | ||
|---|---|---|
A Hybrid CPU-Graphics Processing Unit (GPU) Approach for Computationally Efficient Simulation-Optimization |
Abstract | ||
|---|---|---|
•Simulation-optimization (Sim-Opt) is a widely used, yet computationally expensive optimization technique.•In this paper, we propose a framework for developing a general purpose GPU program for Sim-Opt formulations.•We illustrate the framework using a key variable selection problem in process monitoring solved using a genetic algorithm.•Our results show that very significant acceleration in computation time can be obtained using the GPU. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.compchemeng.2016.01.001 | Computers & Chemical Engineering |
Keywords | Field | DocType |
Genetic Algorithm,Parallel computing,Sim-Opt,PCA,Tennessee Eastman challenge process | Mathematical optimization,Computer science,Acceleration,Graphics processing unit,Genetic algorithm,Computation | Journal |
Volume | ISSN | Citations |
87 | 0098-1354 | 3 |
PageRank | References | Authors |
0.41 | 43 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mai Chan Lau | 1 | 3 | 0.41 |
| Rajagopalan Srinivasan | 2 | 683 | 79.21 |