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Comparison of tabu search and geneti...

Nguyen, Khoa Dang.

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Comparison of tabu search and genetic algorithm in mobile network design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Comparison of tabu search and genetic algorithm in mobile network design./
作者:	Nguyen, Khoa Dang.
面頁冊數:	81 p.
附註:	Source: Masters Abstracts International, Volume: 42-03, page: 0970.
Contained By:	Masters Abstracts International42-03.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1417048

Comparison of tabu search and genetic algorithm in mobile network design.
Nguyen, Khoa Dang.

Comparison of tabu search and genetic algorithm in mobile network design. - 81 p.

Source: Masters Abstracts International, Volume: 42-03, page: 0970.

Thesis (M.Eng.)--University of Louisville, 2003.

This thesis will explore two methods of designing a mobile wireless network. The approaches used in designing their wireless networks are tabu search and genetic algorithm. Both of these methods are widely used for global optimization problems. A detailed network optimization framework is developed for designing wireless network. This optimization problem is then solved using genetic algorithm and tabu search. The designs from the two methods are compared with each other to compare which optimization performs better.Subjects--Topical Terms:

626642
Computer Science.

Comparison of tabu search and genetic algorithm in mobile network design.
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245 1 0 $a Comparison of tabu search and genetic algorithm in mobile network design.
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500 $a Source: Masters Abstracts International, Volume: 42-03, page: 0970.
500 $a Director: Anup Kumar.
502 $a Thesis (M.Eng.)--University of Louisville, 2003.
520 $a This thesis will explore two methods of designing a mobile wireless network. The approaches used in designing their wireless networks are tabu search and genetic algorithm. Both of these methods are widely used for global optimization problems. A detailed network optimization framework is developed for designing wireless network. This optimization problem is then solved using genetic algorithm and tabu search. The designs from the two methods are compared with each other to compare which optimization performs better.
520 $a From the study of the results of this experiment, both of the methods can find a good framework of a mobile wireless network. They both converge at about the same rate. Therefore, they are equal in performance.
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