A proposed swarm intelligent approach for timetable problem / Ahmed sabry Abdelrahman Mohamed ; Supervised Hesham Ahmed Hefny
Material type: TextLanguage: English Publication details: Cairo : Ahmed sabry Abdelrahman Mohamed , 2019Description: 125 Leaves : charts , facsimiles ; 30cmOther title:- أسلوب ذكاء حشود مقترح لحل مشكلة الجداول الزمنية [Added title page title]
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Thesis | قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.18.02.M.Sc.2019.Ah.P (Browse shelf(Opens below)) | Not for loan | 01010110080778000 | |||
CD - Rom | مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.18.02.M.Sc.2019.Ah.P (Browse shelf(Opens below)) | 80778.CD | Not for loan | 01020110080778000 |
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Thesis (M.Sc.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Computer and Information Sciences
Time table problem is a constraint based decision making problem that attracted many researchers over many years due to its importance in several daily life situations. Educational timetable problem is an example of timetable problem. That is quite urgent for any educational institute.Several approaches for solving such a problem appeared over the last four decades however, finding an acceptable solution for such a problem is quite challenging as its computational complexity grow up fast as the number of its parameters increases. Recently, swarm intelligence (SI) techniques have been found to be very effective to solve such highly computational cost problem. SI solving techniques simulate the behaviors of organisms that live in colonies or swarms, e.g. ants, bees, birds,fishes, bats...etc. As the collective behavior of the whole swarm reflects a very effective intelligent behavior. In this thesis, we propose an approach for solving the timetable problem based on a swarm intelligent behavior that found in nature which is called 2vortex behavior3. Vortex behavior is inspired from the P.vortexbacteria that search for food in circular motion. We adopt a (SI) technique called 2vortex swarm optimization3 (VSO) to solve the timetable problem. The proposed VSO solving approach is tested using some unconstraint benchmark problems
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