Speaker
Ji Qiang
(Lawrence Berkeley National Laboratory)
Description
The simultaneous optimization of multiple objective functions is needed in many particle accelerator applications. In this paper, we report on the development of an open source parallel evolution based multi-objective optimization package that uses a variable population from generation to generation and an external storage to save good solutions. Two heuristic optimization methods, one uses the unified differential evolution and the other uses the real-coded genetic algorithm, are included in the optimizer to generate next generation candidate solutions. We will present the usage of the package, tests, and application examples.
| Region represented | North America |
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Primary author
Ji Qiang
(Lawrence Berkeley National Laboratory)
