In 1996, a superconducting magnetic energy storage arrangement was selected to become a benchmark problem for testing different optimization algorithms, both deterministic and stochastic ones. Since the forward problem can be solved semianalytically by Biot-Savart's law, this benchmark became quite popular. Nevertheless, the demands on optimization software have increased dramatically since then. To give an example, methods looking for Pareto-optimal points rather than for a single solution only have been introduced by several groups. In this paper, a proposal for an extended version of the benchmark problem will be made and some results will be presented.
SMES Optimization Benchmark Extended: Introducing Uncertainties and Pareto Optimal Solutions into TEAM22 / P., Alotto; U., Baumgartner; Freschi, Fabio; M., Jaindl; A., Kostinger; C., Magele; W., Renhart; Repetto, Maurizio; G., Steiner. - In: IEEE TRANSACTIONS ON MAGNETICS. - ISSN 0018-9464. - 44:6(2008), pp. 1066-1069. [10.1109/TMAG.2007.916091]
SMES Optimization Benchmark Extended: Introducing Uncertainties and Pareto Optimal Solutions into TEAM22
FRESCHI, FABIO;REPETTO, MAURIZIO;
2008
Abstract
In 1996, a superconducting magnetic energy storage arrangement was selected to become a benchmark problem for testing different optimization algorithms, both deterministic and stochastic ones. Since the forward problem can be solved semianalytically by Biot-Savart's law, this benchmark became quite popular. Nevertheless, the demands on optimization software have increased dramatically since then. To give an example, methods looking for Pareto-optimal points rather than for a single solution only have been introduced by several groups. In this paper, a proposal for an extended version of the benchmark problem will be made and some results will be presented.Pubblicazioni consigliate
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https://hdl.handle.net/11583/1643945
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