2013
DOI: 10.1016/s1874-1029(13)60081-6
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Simulation Optimization: A Review on Theory and Applications

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Cited by 11 publications
(4 citation statements)
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“…For a given simulation, if the number of rescue teams that cover a given demand point i for a certain priority p and period t is h, then the DES model will provide an estimate of T Worked jpt for the h rescue teams and thus will allow to compute q ihpt by using Equation (9). However, the DES model will give no estimates of T Worked jpt for k rescue teams if k6 ¼h to compute q ikpt by using Equation (9).…”
Section: Des Modelmentioning
confidence: 99%
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“…For a given simulation, if the number of rescue teams that cover a given demand point i for a certain priority p and period t is h, then the DES model will provide an estimate of T Worked jpt for the h rescue teams and thus will allow to compute q ihpt by using Equation (9). However, the DES model will give no estimates of T Worked jpt for k rescue teams if k6 ¼h to compute q ikpt by using Equation (9).…”
Section: Des Modelmentioning
confidence: 99%
“…For a given simulation, if the number of rescue teams that cover a given demand point i for a certain priority p and period t is h, then the DES model will provide an estimate of T Worked jpt for the h rescue teams and thus will allow to compute q ihpt by using Equation (9). However, the DES model will give no estimates of T Worked jpt for k rescue teams if k6 ¼h to compute q ikpt by using Equation (9). Thus, we replaced Equation ( 9) by the average of the existing busy fraction estimates for demand nodes that are covered by exactly k rescue teams within S p during period t, which can be formulated as follows:…”
Section: Des Modelmentioning
confidence: 99%
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“…These simulation runs will be undertaken for the parameter values chosen from the sampling method utilised, to obtain the most information about the constrained design space. Using the outputs from the selected simulation runs, a "meta-model" can be constructed to describe the relationship between x n and f (x n ) (Wang and Shi 2013). Therefore, reducing the CPU cost associated with running multiple simulations, as only the n sample points are required.…”
Section: The Optimisation Processmentioning
confidence: 99%