Optimization of air pollutant monitoring stations with constraints using genetic algorithm

Issue title: Emerging services and technologies in wireless networks

Guest editors: Jin Li, Fatos Xhafa and Jian Weng

Article type: Research Article

Authors: Wang, Kai^a | Zhao, Hong^{a; *} | Ding, Yanan^a | Li, Tao^a | Hou, Lujian^b | Sun, Fengjuan^b

Affiliations: [a] College of Information Technical Science, NanKai University, Tianjin, China. E-mail: [email protected] | [b] Jinan Academy of Environmental Protection Science, Jinan, China. E-mail: [email protected]

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: The design of air quality monitoring stations (AQMS) is very important for environmental protection department. The task, however, has been proven to be in the class of nondeterministic polynomial (NP)-hard problem. The powerful search capability of the genetic algorithm (GA) is helpful for selecting optimal monitoring sites. A mathematical programming model based method is proposed, in which environmental, social and economical factors are considered and the GA is used to optimize AQMS. Modelling results indicate that the proposed method outperforms the method of random site of AQMS. The proposed method/framework is also suitable for the design of communication network. For example, the wireless base stations can be well placed by similar method, providing sufficient signal strength for better service with lower cost.

Keywords: Air pollution monitoring sites, genetic algorithm, optimization, constraints

DOI: 10.3233/JHS-150516

Journal: Journal of High Speed Networks, vol. 21, no. 2, pp. 141-153, 2015