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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Salwani Abdullah, Prof. Dr. | |
| dc.contributor.author | Ayad Mashaan Turky (P63382) | |
| dc.date.accessioned | 2023-10-06T09:15:49Z | - |
| dc.date.available | 2023-10-06T09:15:49Z | - |
| dc.date.issued | 2013-01-18 | |
| dc.identifier.other | ukmvital:81146 | |
| dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/476285 | - |
| dc.description | Many optimisation problems are dynamic in the sense that changes occur during the optimisation process, and therefore are more challenging than the stationary problems. The occurrences of such problems have attracted researchers into studying areas of artificial intelligence and operational research. To solve dynamic optimisation problems, the proposed approaches should not only attempt to seek the global optima but be able to also keep track of changes in the landscape solutions. Population-based approaches have been intensively investigated to address these problems, as solutions are scattered over the entire search space and therefore helps in recognizing any changes that occur in the search space. However, optimisation algorithms that have been used to solve stationary problems cannot be directly applied to handle dynamic problems without any modifications such as in maintaining population diversity. The research work presented in this thesis aims to build upon the state of the art in search methodologies for dynamic optimisation problems, where a hybrid harmony search algorithm which is one of the most recent new population-based meta-heuristic methods is employed. This algorithm mimics the musical process when a musician attempts to find a state of harmony. In order to cope with a dynamic behaviour, the proposed harmony search algorithm is hybridised with a (i) random immigrant, (ii) memory mechanism and (iii) memory based immigrant scheme. The main goal of these mechanisms is maintain the population diversity through updating them from time to time based on the changes occurrences. This hybridisation processes can help to keep track of the changes and to maintain the population diversity. The performance of the proposed hybrid harmony search is verified by using the well-known dynamic test problem called the Moving Peak Benchmark (MPB) with a variety of peaks. The empirical results demonstrate that the proposed algorithm is able to obtain competitive results, if not the best for most of the cases, when compared to the best known results in the scientific literature published so far.,Master of Information Technology | |
| dc.language.iso | eng | |
| dc.publisher | UKM, Bangi | |
| dc.relation | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
| dc.rights | UKM | |
| dc.subject | Harmonic analysis | |
| dc.subject | Heuristic algorithms | |
| dc.subject | Algorithms | |
| dc.subject | Mathematical optimization | |
| dc.subject | Universiti Kebangsaan Malaysia -- Dissertations | |
| dc.subject | Dissertations, Academic -- Malaysia | |
| dc.title | A hybrid harmony search algorithm for dynamic optimisation problems | |
| dc.type | theses | |
| dc.format.pages | 73 | |
| dc.identifier.callno | QA403.T846 2013 3 tesis | |
| Appears in Collections: | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_81146+Source01+Source010.PDF Restricted Access | 1.25 MB | Adobe PDF |  View/Open |
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