MARC details
| 000 -LEADER |
|---|
| fixed length control field |
06539namaa22004331i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
EG-GICUC |
| 005 - أخر تعامل مع التسجيلة |
|---|
| control field |
20260209151412.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
260209s2025 ua a|||frm||| 000 0 eng d |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloguing agency |
EG-GICUC |
| Language of cataloging |
eng |
| Transcribing agency |
EG-GICUC |
| Modifying agency |
EG-GICUC |
| Description conventions |
rda |
| 041 0# - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| Language code of summary or abstract |
eng |
| -- |
ara |
| 049 ## - Acquisition Source |
|---|
| Acquisition Source |
Deposit |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
658.4034 |
| 092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC) |
|---|
| Classification number |
658.4034 |
| Edition number |
21 |
| 097 ## - Degree |
|---|
| Degree |
Ph.D |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
|---|
| Local Call Number |
Cai01.18.05.Ph.D.2025.Mo.I |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
|---|
| Authority record control number or standard number |
Mohammed Adnan Jawad AL-Azzawi, |
| Preparation |
preparation. |
| 245 13 - TITLE STATEMENT |
|---|
| Title |
An improved gaining-sharing knowledge based algorithm to solve optimization problems / |
| Statement of responsibility, etc. |
by Mohammed Adnan Jawad AL-Azzawi ; Supervised Prof. Ali Wagdy Mohamed, Dr. Heba Sayed Mohamed Roshdy. |
| 246 15 - VARYING FORM OF TITLE |
|---|
| Title proper/short title |
خوارزمية محسنة إكتساب ومشاركة المعرفة لحل مشاكل الامثلية |
| 264 #0 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
2025. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
153 Leaves : |
| Other physical details |
illustrations ; |
| Dimensions |
30 cm. + |
| Accompanying material |
CD. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rda content |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
Unmediated |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Source |
rdacarrier |
| 502 ## - DISSERTATION NOTE |
|---|
| Dissertation note |
Thesis (Ph.D)-Cairo University, 2025. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Bibliography: pages 137-153 |
| 520 #3 - SUMMARY, ETC. |
|---|
| Summary, etc. |
In recent times, the Gaining-Sharing Knowledge-based algorithm (GSK) has arguably been one of the most powerful and versatile evolutionary optimizers for continuous parameter spaces, drawing inspiration from the ways humans acquire and exchange knowledge. Its various improvements and modifications set it apart as a strong contender in the realm of metaheuristic optimization algorithms. This thesis presents an enhanced version of the Gaining-Sharing Knowledge-based algorithm (eGSK) to solve optimization problems that don't have limits in a continuous space. This algorithm is based on adaptive methods that aim to mitigate the problem of premature convergence during the search process. The modification is fundamentally inspired by the principles of Adjust Selection Criteria, Modify Parameters Setup, and Escape from Local Minimum Solution, respectively. We conducted comparisons and statistical tests with the GSK and other algorithms to verify and analyze the performance of the eGSK algorithm. It was done by performing numerical experiments on 29 test problem sets in 10, 30, 50, and 100 dimensions from the Congress on Evolutionary Computation (CEC) 2017 benchmark. The results were compared with three GSK variant algorithms, seven state-of-the-art algorithms, and GSK alongside components of the eGSK algorithm. According to test results, the eGSK algorithm performs exceptionally well at solving optimization problems with 30, 50, and 100 dimensions and is competitive in 10 dimensions. Finally, the eGSK algorithm has been applied to solve a set of 22 real-world optimization problems from the CEC 2011. The results were compared with 14 state-of-the-art algorithms. The eGSK provided more effective solutions for real-world optimization problems, ultimately ranking as the top optimizer with superior performance compared to other algorithms. Therefore, this means the proposed eGSK algorithm outperforms its competitors and achieves more competitive results, especially with high-dimensional problems. |
| 520 #3 - SUMMARY, ETC. |
|---|
| Summary, etc. |
في الآونة الأخيرة، تُعدّ خوارزمية اكتساب المعرفة ومشاركتها (GSK) من أقوى وأكثر الخوارزميات التطورية تنوعًا في فضاءات المعلمات المتصلة، مستلهمة من طرق اكتساب البشر للمعرفة وتبادلها. وتتميز بتحسيناتها وتعديلاتها المتنوعة كمنافس قوي في مجال خوارزميات التحسين الاستدلالي. تُقدّم هذه الرسالة نسخة مُحسّنة من خوارزمية اكتساب المعرفة ومشاركتها (eGSK) لحل مسائل التحسين غير المقيدة في فضاءات المعلمات المتصلة. تعتمد هذه الخوارزمية على أساليب تكيفية تهدف إلى التخفيف من مشكلة التقارب المبكر أثناء عملية البحث. تستلهم هذه التعديلات أساسًا من مبادئ "ضبط معايير الاختيار"، و"تعديل إعدادات المعلمات"، و"الهروب من الحد الأدنى المحلي للحل"، على التوالي. أجرينا مقارنات واختبارات إحصائية مع خوارزمية GSK وخوارزميات أخرى للتحقق من أداء خوارزمية eGSK. تم ذلك من خلال إجراء تجارب عددية على 29 مجموعة من مشاكل الاختبار في 10 و30 و50 و100 بُعد من معيار مؤتمر الحوسبة التطورية (CEC) 2017. تمت مقارنة النتائج بثلاث خوارزميات متغيرة من GSK وسبع خوارزميات متطورة وGSK إلى جانب مكونات خوارزمية eGSK. وفقًا لنتائج الاختبار، تعمل خوارزمية eGSK بشكل جيد للغاية في حل مشاكل التحسين ذات الأبعاد 30 و50 و100 وهي تنافسية في 10 أبعاد. أخيرًا، كما تم تطبيق خوارزمية eGSK لحل مجموعة من 22 مشكلة تحسين واقعية من CEC 2011. تمت مقارنة النتائج بـ 14 خوارزمية متطورة. قدمت eGSK حلولاً أكثر فعالية لمشاكل التحسين الواقعية، واحتلت في النهاية المرتبة الأولى كأفضل مُحسِّن بأداء متفوق مقارنة بالخوارزميات الأخرى. وبالتالي، فإن هذا يعني أن خوارزمية eGSK المقترحة تتفوق على منافسيها وتحقق نتائج أكثر تنافسية، خاصة مع المشاكل ذات الأبعاد العالية. |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
|---|
| Issues CD |
Issues also as CD. |
| 546 ## - LANGUAGE NOTE |
|---|
| Text Language |
Text in English and abstract in Arabic & English. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Operations Research and Management |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
بحوث وإدارة العمليات |
| 653 #1 - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Human-related techniques |
| -- |
Optimal solutions, |
| -- |
Meta-heuristics |
| -- |
Optimizations |
| -- |
Gaining-Sharing knowledge-based algorithm |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ali Wagdy Mohamed |
| Relator term |
thesis advisor. |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Heba Sayed Mohamed Roshdy |
| Relator term |
thesis advisor. |
| 900 ## - Thesis Information |
|---|
| Grant date |
01-01-2025 |
| Supervisory body |
Ali Wagdy Mohamed |
| -- |
Heba Sayed Mohamed Roshdy |
| Universities |
Cairo University |
| Faculties |
Faculty of Graduate Studies for Statistical Research |
| Department |
Department of Operations Research and Management |
| 905 ## - Cataloger and Reviser Names |
|---|
| Cataloger Name |
Shimaa |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Thesis |
| Edition |
21 |
| Suppress in OPAC |
No |