DocumentCode
190044
Title
Cabling and cost optimization system for IP based networks through Genetic Algorithm
Author
Balubal, Charmaine B. ; Bernardo, Angela Rachel D. ; Lasheras, Bryan Lloyd L. ; Uyehara, Regina A. ; Bandala, Argel A. ; Dadios, Elmer P.
Author_Institution
Dept. of Comput. Sci., Polytech. Univ. of the Philippines, Manila, Philippines
fYear
2014
fDate
14-16 April 2014
Firstpage
351
Lastpage
355
Abstract
The creation of an optimized cabling plan in terms of cost through optimized cable length was introduced in this study. The researchers designed a system that utilized Genetic Algorithm for the said optimization. This system was integrated in a graphical user interface created using visual c# language which enables the users to upload an image representing the floor plan of the desired network to be optimized. The user can then place specified components on the floor plan. Lastly, the system will generate the optimized cabling plan which the user can readily print. Furthermore, a complete bill of materials and costing report will be generated also. The system generated these outputs by using genetic algorithm in the graphical inputs which were processed and converted in numerical representations. Upon accomplishing all the experimentations, the system yielded 99.51% optimization accuracy with 99.02% as the highest optimization level generated after accomplishing 100 trials on 10 different floor plans.
Keywords
C language; IP networks; genetic algorithms; graphical user interfaces; numerical analysis; IP based networks; cable length; cabling optimization system; cost optimization system; floor plan; genetic algorithm; graphical inputs; graphical user interface; numerical representations; optimized cabling; visual c# language; Bills of materials; Coaxial cables; Floors; Genetic algorithms; Optical fiber cables; Optimization; Power cables; Genetic Algorithm; IP networks; Network Cabling; Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Region 10 Symposium, 2014 IEEE
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4799-2028-0
Type
conf
DOI
10.1109/TENCONSpring.2014.6863056
Filename
6863056
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