Name
Abstract | ||
|---|---|---|
A lot of problems in control engineering aim at solving discrete-event systems in presence of performance measure constraints. In many cases, these problems are most suitable to be modeled as constrained simulation optimization, and a key question for solving these problems is to efficiently and accurately select all the feasible designs from a finite set of design alternatives. In this paper, we consider the feasibility determination problem in presence of multiple performance measure constraints. By making some asymptotic approximation, we derive the optimal solution to maximize the expected number of correct selection for all the designs. A corresponding sequential selection procedure is designed for implementation. Numerical testing shows that our approach considerably enhances the simulation efficiency. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICIT.2016.7474887 | PROCEEDINGS 2016 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT) |
Field | DocType | Citations |
Resource management,Sequential selection,Mathematical optimization,Finite set,Numerical models,Numerical testing,Control theory,Frequency-division multiplexing,Atmospheric model,Expected value,Engineering | Conference | 1 |
PageRank | References | Authors |
0.36 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siyang Gao | 1 | 80 | 11.83 |
| Weiwei Chen | 2 | 125 | 12.21 |