Research of Applying Genetic Alogrithm to Design Data Warehouse and Performance analysis
| Autor: | Wen-Yi Liu, 劉文義 |
|---|---|
| Rok vydání: | 2005 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 93 Today, maintenance management has been one of the most important tasks in manufacturing. The aims of maintenance strategies are to reduce maintenance costs while improving maintenance operation and to help the maintenance managers to make the right decision at the right time in the right place. Computerized maintenance management systems(CMMS) can help us to deal with these maintenance tasks, but doesn’t have Decision Support System (DSS) capability. In this thesis, we design a data warehouse for Equipment Management System(EMS) to help the manager inquire and make decision by different dimension in a quickly and flexible way. Many cubes, such as MTTR, MTBF, Spare response time,… are created using the flake schemas. Finally, some concluding remarks are made. The results of this research will also provide a reference model for enterprise when EMS data warehouise is evaluated as a To Be system. For data cube selection, in order to minimize query time under the storage limit, we adopt partial materialized way to select data cubes. In this thesis, we use three ways to select data cubes：Greedy algorithm, FGS+GA, which incorporate genetic algorithm with forward greedy algorithm and BGS+GA, which incorporates genetic algorithm with forward greedy algorithm. According to our experiments, in case of most of storage constraint, the solution generated by FGS+GA is as well as the solution generated by BGS+GA, and both of them is superior to that found by Greedy algorithm. Furthermore, when we compare the efficiency of FGS+GA with BGS+GA, we find that the efficiency of FGS+GA is superior to BGS+GA. For performance anlysis, we compare the query time and space utilication of the selected cubes obtained by method we proposed with all materialized way. According to our experiments, the results obtained from our method can decrease 70% of storage space, and the query time of our method is as well as all materialized way. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|