Name
Abstract | ||
|---|---|---|
Engineering design increasingly uses computer simulation models coupled with optimization algorithms to find the best design that meets the customer constraints within a time constrained deadline. The continued application of Moore's law combined with linear speedups of coarse grained parallelization will allow more designs to be evaluated in shorter periods of time. This paper presents a scalable, standards based framework that uses web services and grid services with a multiple objective genetic algorithm to solve continuous, mixed integer, single objective or multiple objective nonlinear, constrained design problems. Test data is provided to validate a linear speedup based on the number of processors and to show the robustness of the genetic algorithm on a set of 10 design problems. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1276958.1277372 | GECCO |
Keywords | Field | DocType |
constrained optimization,genetic algorithm,service oriented architecture,design patterns,web services,web service,computer simulation,engineering design | Mathematical optimization,Computer science,Software design pattern,Robustness (computer science),Engineering design process,Web service,Genetic algorithm,Service-oriented architecture,Grid,Speedup | Conference |
Citations | PageRank | References |
2 | 0.45 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David J. Powell | 1 | 152 | 39.83 |
| Joel Hollingsworth | 2 | 12 | 3.20 |