In this research, we designed and implemented optimization search algorithms to facilitate implementation of optimization search software. We provided the design of module interaction graph including modules, ports, and channels. We can map solving algorithms of sub-problems onto behavioral designs incorresponding modules. Finally, they can integrate module¡¦s with channels. Since optimization search algorithms may evolve one to several solutions at the same time, we planned a solution set organization to support designer-planned search strategy. During the optimization process, solutions or sub-solutions should be evaluated and analyzed. Because excessive executive time as commonly spent in replicated evaluation, we planned dynamic programming for reusing evaluation results to reduce replicated evaluation time. Lastly, when evolving new solutions, usually only a small number of decisions are changed. We planed a hierarchical decision representation and maintenance operations to reduce replication of common parts among solutions to further enhance its execution speed.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0905108-153025 |
| Date | 05 September 2008 |
| Creators | Zhong, Da-jun |
| Contributors | Chia-hsiung Kao, Chih-chen Chen, Tsung Lee |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905108-153025 |
| Rights | not_available, Copyright information available at source archive |
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