Discrete optimization via simulation with stochastic constraints
In this thesis, we first develop a new method called penalty function with memory (PFM). PFM consists of a penalty parameter and a measure of constraint violation and it converts a discrete optimization via simulation (DOvS) problem with stochastic constraints into a series of DOvS problems without...
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| Format: | Others |
| Language: | en_US |
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Georgia Institute of Technology
2013
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| Online Access: | http://hdl.handle.net/1853/49088 |