Adaptive genetic algorithm for production system

Other Title(s)

تحسين أداء خوارزمية الخريطة الجينية في أنظمة الإنتاج

Dissertant

al-Sayidah, Majdi Jalil

Thesis advisor

al-Mashaikhi, Akram Muhammad Uthman

Comitee Members

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

University

Amman Arab University

Faculty

Collage of Computer Sciences and Informatics

Department

Department of Computer Science

University Country

Jordan

Degree

Master

Degree Date

2013

English Abstract

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.

Main Subjects

Mathematics

Topics

• Algorithms
• Self
• Adaptive control systems

No. of Pages

62

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-526496