Property | Value |
Name | NCL-TR-2007006 |
Description |
Enabling the Extended Compact Genetic Algorithm for Real-Parameter Optimization by using Adaptive Discretization
Abstract: This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable probabilistic model building genetic algorithms (PMBGAs) to solve optimization problems in the continuous domain. The procedure, effect, and usage of SoD are described in detail. As an example of using SoD with PMBGAs, the integration of SoD and the extended compact genetic algorithm (ECGA), named real-coded ECGA (rECGA), is proposed and numerically examined in the study. The numerical experiments include a set of benchmark functions and a real-world application, the economic dispatch problem. The results on the benchmark functions indicate that SoD is a better discretization method than two well-known methods: the fixed-height histogram (FHH) and the fixed-width histogram (FWH). Moreover, the experimental results on the economic dispatch problems demonstrate that rECGA works quite well, and the solutions better than the best known results presented in the literature are achieved. |
Filename | NCL-TR-2007006.pdf |
Filesize | 282.69 kB |
Filetype | pdf (Mime Type: application/pdf) |
Creator | ypchen |
Created On: | 03/24/2007 23:44 |
Viewers | Everybody |
Maintained by | Publisher |
Hits | 3327 Hits |
Last updated on | 12/09/2010 14:28 |
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