Adaptive genetic algorithm for production system

العناوين الأخرى

تحسين أداء خوارزمية الخريطة الجينية في أنظمة الإنتاج

مقدم أطروحة جامعية

al-Sayidah, Majdi Jalil

مشرف أطروحة جامعية

al-Mashaikhi, Akram Muhammad Uthman

أعضاء اللجنة

al-Ani, Muzhir Shaban
al-Mashaqibah, Firas Faris Musa

الجامعة

جامعة عمان العربية

الكلية

كلية العلوم الحاسوبية و المعلوماتية

القسم الأكاديمي

قسم علم الحاسوب

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2013

الملخص الإنجليزي

In recent years, with the great competitive in the market place, many researchers proposed methods and algorithms that aim to find adaptive optimization strategies to solve the problem of planning and scheduling in manufacturing systems.

Such kind of studies fall under the list of artificial intelligence and interest in the acquisition of the knowledge of God, and enable them to make and implement decisions on behalf of the human.

Here is evident obvious difference between artificial intelligence and object-oriented programming, where the latter does not have the ability to make decisions alone should be available directs the user to what you should do its work.

The idea thesis of difference in views between officials of the production companies, as some of them had to give the machine a specific type of products for the completion of the process addressed first and start another type, while the other section to distribute more than one product on more than one machine where the processed productby special machine which, where this method helps us to achieve the exploitation and optimum utilization of available resources in the factory.

It is the principle of achieving major benefit and the parable of the exploitation of resources have put forward in our project several methodologies(on the shelf), It helps a genetic algorithm to find the ideal distribution of products via the available resources in a random manner, based on the equations, especially in genetic algorithmwhere the results showed a significant improvement compared to when applying the algorithm before the amendment, when you return to the improvement for the cost, we will find it reached the amount of 25%, while the improvement in terms of stability for the production lines is about 73%, either in terms of time used to handle a particular product was improved approximately 36 % Finally, the size of the representation of the product has been reduced to the simplest form to be treated and it have reached 30% than it was when the application of genetic algorithm.

التخصصات الرئيسية

الرياضيات

الموضوعات

عدد الصفحات

62

قائمة المحتويات

Table of contents.

Abstract.

Abstract in Arabic.

Chapter One : Introduction.

Chapter Two : Literature review.

Chapter Three : Problem description and analysis.

Chapter Four : Results and analysis.

Chapter Five : Conclusions.

References.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

al-Sayidah, Majdi Jalil. (2013). Adaptive genetic algorithm for production system. (Master's theses Theses and Dissertations Master). Amman Arab University, Jordan
https://search.emarefa.net/detail/BIM-526496

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

al-Sayidah, Majdi Jalil. Adaptive genetic algorithm for production system. (Master's theses Theses and Dissertations Master). Amman Arab University. (2013).
https://search.emarefa.net/detail/BIM-526496

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

al-Sayidah, Majdi Jalil. (2013). Adaptive genetic algorithm for production system. (Master's theses Theses and Dissertations Master). Amman Arab University, Jordan
https://search.emarefa.net/detail/BIM-526496

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-526496