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A chaos search approach to optimization problems / Mohamed Fathi Goda Elsantawy ; Supervised Abdulhadi Nebih Ahmed , Ramadan Abdelhameed Zean Eldean

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohamed Fathi Goda Elsantawy , 2015Description: 159 Leaves ; 30cmOther title:
  • أ{uئإآ٣}{uئإإ٠}{uئإإإ}ب {uئإؤ٣}{uئإإإ}{uئإآئ}{uئإإإ}ى {uئإؤئ}{uئإإ٤}{uئإآ٨}{uئإ٨إ}{uئإؤآ}{uئإؤإ} أ{uئإإ٣}{uئإ٩أ}{uئإإ٠}{uئآئئ}{uئإ٩٤} [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Operations Research Summary: In this thesis work, we introduce a big picture of merging two areas; chaos and optimization. We try to address the features of this merge, borders, limitations, and optimal methods of incorporations of chaos to optimization. Three main areas of optimization were studied for chaos combination; evolutionary algorithms (EAs), multi - objective optimization (MOP), and multi - criteria decision making (MCDM). We proposed chaotic topology for swarm intelligent techniques in EAs field, chaotic external archive scheme for the multi - objective evolutionary algorithms (MOEAs) field, and finally polynomial chaos for MCDM field. For the first and second areas; suitable benchmarks, metrics, and test functions are adopted for comparisons and experiments. Several proposed chaotic algorithms are illustrated in both single and multi - objective versions. For MCDM, five real-life categories of applications are illustrated and presented
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.05.Ph.D.2015.Mo.C (Browse shelf(Opens below)) Not for loan 01010110067209000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.05.Ph.D.2015.Mo.C (Browse shelf(Opens below)) 67209.CD Not for loan 01020110067209000

Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Operations Research

In this thesis work, we introduce a big picture of merging two areas; chaos and optimization. We try to address the features of this merge, borders, limitations, and optimal methods of incorporations of chaos to optimization. Three main areas of optimization were studied for chaos combination; evolutionary algorithms (EAs), multi - objective optimization (MOP), and multi - criteria decision making (MCDM). We proposed chaotic topology for swarm intelligent techniques in EAs field, chaotic external archive scheme for the multi - objective evolutionary algorithms (MOEAs) field, and finally polynomial chaos for MCDM field. For the first and second areas; suitable benchmarks, metrics, and test functions are adopted for comparisons and experiments. Several proposed chaotic algorithms are illustrated in both single and multi - objective versions. For MCDM, five real-life categories of applications are illustrated and presented

Issued also as CD

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