MARC details
| 000 -LEADER |
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| fixed length control field |
03115ntm a2200337 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
MY-KuUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20260403161604.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
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t||||fr|||| 000 0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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ta |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
260403t20252025my a|||fr|||| 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0010431 (Local) |
| Qualifying information |
Hardback |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UMPSA |
| Language of cataloging |
eng |
| Transcribing agency |
UMPSA |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FKOM .A89 2025 r Thesis |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Nurul Asyikin Binti Zainal, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
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| Title |
Enhancing the symbiotic organisms search algorithm with fuzzy adaptive selection / |
| Statement of responsibility, etc. |
Nurul Asyikin Binti Zainal |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Kuantan, Pahang : |
| Name of producer, publisher, distributor, manufacturer |
UMPSA, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2025 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
© 2025 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xv, 182 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
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| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
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| Source |
rdacarrier |
| Carrier type term |
volume |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
|---|
| Source |
rda |
| File type |
text file |
| Encoding format |
PDF |
| 500 ## - GENERAL NOTE |
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| General note |
Faculty of Computing |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang Al Sultan Abdullah - 2025 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Include bibliographical reference |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
The Symbiotic Organism Search (SOS) algorithm has recently attracted significant attention due to its superior performance compared to other metaheuristic algorithms. A key advantage of SOS is its reliance on three distinct search phases (based on three update operators) and does not rely on any parameter controls. On the one hand, the three update operators work well (i.e., mutualism, commensalism, and parasitism) among each other and relieve the need to do significant tuning of any control parameters. On the other hand, not having any control parameters can also be a potential drawback. In the current form, SOS has a pre-set sequence for exploration (searching through the entire solution space) and exploitation (utilizing the known local best) beginning from commensalism, mutualism, and parasitism update operators. Having a pre-set sequence can be counter-productive because the search process becomes insensitive to the current needs of the optimization, which could lead to premature convergence or getting trapped in local optima by not adapting dynamically to the problem's requirements. To address these issues, this thesis proposes an adaptive fuzzy-based SOS variant called Fuzzy Symbiotic Optimization Search (FSOS). Based on the use of Mamdani fuzzy, FSOS can select one or a combination of the mutualism, commensalism, and parasitism update operators by adjusting their individual probabilities through fuzzy decision-making. FSOS was tested on 23 benchmark functions and applied to a t-way test generation case study to assess its effectiveness. The experimental results show that FSOS delivers competitive performance, surpassing its predecessor (SOS) and other metaheuristic algorithms with a 95% confidence level. Overall, the findings demonstrate the potential of a parameter-free adaptive algorithm in solving general optimization problems, making them relevant for scientific research and practical applications. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
Faculty of Computing |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Universities and colleges |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Theses |
| General subdivision |
Dissertations |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Thesis |