Optimization of multi-resource allocation in large-scale project management
Dissertant
Thesis advisor
University
Isra University
Faculty
Faculty of Engineering
University Country
Jordan
Degree
Master
Degree Date
2015
English Abstract
Project can be classified to small, medium, large and very large.
This could be mainly based on number of activities, the budget of the project or the completion time.
The criterion of scaling could be change from country to another.
In this project, it is assumed that as the number of activities increase, the scale is increased.
This thesis develops an algorithm to generate a unique Activity On Arrow (AOA) network with a minimum number of dummy activities.
It also develops an algorithm to deal with multi resources, by generating a new resource, which is in relation to all considered resources by a defined expression.
A Genetic Algorithm is used in order to perform resource leveling and allocation in the large-scale project.
The developed algorithm is based on shifting the noncritical activities within their total float to reduce the undesired fluctuation.
IV Four indices are considered to determine the optimum scheduling process.
A mathematical model is developed to consider these indices by creating a weight for each one; a simulation is applied in developed MATLAB program to reach to the best weights that achieve the optimum scheduling.
The efficiency of the proposed algorithm is measured by the resource improvement coefficient.
As a case-study, an expansion took place of the Irbid Specialized Hospital project, in Irbid-Jordan, is used to explore the application of the proposed algorithm.
For this real case, the proposed algorithm gives almost normal distribution shape of the activity leveling, which validates the algorithm applicability.
Main Subjects
Business Administration
Information Technology and Computer Science
Topics
No. of Pages
130
Table of Contents
Table of contents.
Abstract.
Chapter One : Introduction.
Chapter Two : Literature review.
Chapter Three : Scheduling process based genetic algorithm.
Chapter Four : Results and analysis.
Chapter Five : Conclusions and future works.
References.
American Psychological Association (APA)
al-Qnahrah, Amir Muhammad. (2015). Optimization of multi-resource allocation in large-scale project management. (Master's theses Theses and Dissertations Master). Isra University, Jordan
https://search.emarefa.net/detail/BIM-596808
Modern Language Association (MLA)
al-Qnahrah, Amir Muhammad. Optimization of multi-resource allocation in large-scale project management. (Master's theses Theses and Dissertations Master). Isra University. (2015).
https://search.emarefa.net/detail/BIM-596808
American Medical Association (AMA)
al-Qnahrah, Amir Muhammad. (2015). Optimization of multi-resource allocation in large-scale project management. (Master's theses Theses and Dissertations Master). Isra University, Jordan
https://search.emarefa.net/detail/BIM-596808
Language
English
Data Type
Arab Theses
Record ID
BIM-596808
