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A problem of upgrading to the Next Generation Wireless Network NGWN is backward compatibility with pre-existing networks, the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. In this paper, we propose a new genetic algorithm has double population to solve Multi-Objectives Optimal of Upgrading Infrastructure MOOUI problem in NGWN. We modeling network topology for MOOUI problem has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. Our objective function is the sources to concentrators connectivity cost as well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We generate two populations satisfy constraints and combine them to build solutions and evaluate the performance of my algorithm with data randomly generated. Numerical results show that our algorithm is a promising approach to solve this problem.

KEYWORDS

Multi-Objectives Optimal; Next Generation Wireless Network; Network Design; Capacity Planning; Genetic Algorithm; Two-populations

Cite this paper

Le, D. , Nguyen, N. , Ha, D. and Le, V. 2013 A New Genetic Algorithm Applied to Multi-Objectives Optimal of Upgrading Infrastructure in NGWN. Communications and Network, 5, 223-231. doi: 10.4236-cn.2013.53B2042.





Autor: Dac-Nhuong Le, Nhu Gia Nguyen, Dac Binh Ha, Vinh Trong Le

Fuente: http://www.scirp.org/



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