Name
Abstract | ||
|---|---|---|
Complex system configuration problems are the problems of appropriately assigning system parameter values for optimizing some aspect of complex system performance. In this paper, we first cast complex system configuration problems as mixed-variable parameter optimization problems where mensurable system simulation responses are used for evaluation. Then we present a simulation-based ant colony optimization algorithm (sACOMV) to tackle the problems. In sACOMV the decision variables of the complex system configuration problems can be clearly declared as continuous, ordinal, or categorical and let the algorithm treat them adequately. Finally, sACOMV is tested on mixed-variable complex engineering system configuration problems. The effectiveness and robustness of sACOMV are demonstrated by the comparisons with results from the literature. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SYSOSE.2014.6892497 | SoSE |
Keywords | Field | DocType |
ant colony optimisation,sacomv algorithm,ant colony optimization,parameter estimation,mixed-variable parameter optimization problems,simulation responses,ordinal variable,categorical variable,mixed variables,continuous variable,system parameter values,large-scale systems,simulation-based ant colony optimization,complex system configuration problems,decision variables,probabilistic logic,linear programming,optimization | Ant colony optimization algorithms,Decision variables,Mathematical optimization,Categorical variable,Computer science,Ordinal number,Robustness (computer science),Optimization problem,Metaheuristic | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianjun Liao | 1 | 0 | 0.34 |
| Ruijun Li | 2 | 0 | 0.34 |
| Guangrong You | 3 | 0 | 0.34 |
| Ke-wei Yang | 4 | 193 | 22.65 |