Methods to compare expensive stochastic optimization algorithms with application to road design
Analyzing test data of stochastic optimization algorithms under random restarts is challenging. The data needs to be resampled to estimate the behavior of the incumbent solution during the optimization process. The estimation error needs to be understood in order to make reasonable inference on the...
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| Language: | English |
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University of British Columbia
2017
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| Online Access: | http://hdl.handle.net/2429/62097 |