Cabling and cost optimization system for IP based networks through genetic algorithm

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# langua...

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المؤلفون الرئيسيون: Balubal, Charmaine B., Bernardo, Angela Rachel D., Lasheras, Bryan Lloyd L., Uyehara, Regina A., Bandala, Argel A., Dadios, Elmer P.
التنسيق: text
منشور في: Animo Repository 2014
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الوصول للمادة أونلاين:https://animorepository.dlsu.edu.ph/faculty_research/3357
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4359/type/native/viewcontent/tenconspring.2014.6863056
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المؤسسة: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-43592021-09-06T07:06:57Z Cabling and cost optimization system for IP based networks through genetic algorithm Balubal, Charmaine B. Bernardo, Angela Rachel D. Lasheras, Bryan Lloyd L. Uyehara, Regina A. Bandala, Argel A. Dadios, Elmer P. 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. © 2014 IEEE. 2014-07-23T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/3357 info:doi/10.1109/tenconspring.2014.6863056 https://animorepository.dlsu.edu.ph/context/faculty_research/article/4359/type/native/viewcontent/tenconspring.2014.6863056 Faculty Research Work Animo Repository Cables Internet Protocol multimedia subsystem Genetic algorithms Electrical and Computer Engineering Electrical and Electronics
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Cables
Internet Protocol multimedia subsystem
Genetic algorithms
Electrical and Computer Engineering
Electrical and Electronics
spellingShingle Cables
Internet Protocol multimedia subsystem
Genetic algorithms
Electrical and Computer Engineering
Electrical and Electronics
Balubal, Charmaine B.
Bernardo, Angela Rachel D.
Lasheras, Bryan Lloyd L.
Uyehara, Regina A.
Bandala, Argel A.
Dadios, Elmer P.
Cabling and cost optimization system for IP based networks through genetic algorithm
description 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. © 2014 IEEE.
format text
author Balubal, Charmaine B.
Bernardo, Angela Rachel D.
Lasheras, Bryan Lloyd L.
Uyehara, Regina A.
Bandala, Argel A.
Dadios, Elmer P.
author_facet Balubal, Charmaine B.
Bernardo, Angela Rachel D.
Lasheras, Bryan Lloyd L.
Uyehara, Regina A.
Bandala, Argel A.
Dadios, Elmer P.
author_sort Balubal, Charmaine B.
title Cabling and cost optimization system for IP based networks through genetic algorithm
title_short Cabling and cost optimization system for IP based networks through genetic algorithm
title_full Cabling and cost optimization system for IP based networks through genetic algorithm
title_fullStr Cabling and cost optimization system for IP based networks through genetic algorithm
title_full_unstemmed Cabling and cost optimization system for IP based networks through genetic algorithm
title_sort cabling and cost optimization system for ip based networks through genetic algorithm
publisher Animo Repository
publishDate 2014
url https://animorepository.dlsu.edu.ph/faculty_research/3357
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4359/type/native/viewcontent/tenconspring.2014.6863056
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