A Memetic Algorithm for the location-based continuously operating reference stations placement problem in Network Real-Time Kinematic

Tang, Maolin (2015) A Memetic Algorithm for the location-based continuously operating reference stations placement problem in Network Real-Time Kinematic. IEEE Transactions on Cybernetics, 45(10), pp. 2214-2223.

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Abstract

Network Real-Time Kinematic (NRTK) is a technology that can provide centimeter-level accuracy positioning services in real time, and it is enabled by a network of Continuously Operating Reference Stations (CORS). The location-oriented CORS placement problem is an important problem in the design of a NRTK as it will directly affect not only the installation and operational cost of the NRTK, but also the quality of positioning services provided by the NRTK. This paper presents a Memetic Algorithm (MA) for the location-oriented CORS placement problem, which hybridizes the powerful explorative search capacity of a genetic algorithm and the efficient and effective exploitative search capacity of a local optimization. Experimental results have shown that the MA has better performance than existing approaches. In this paper we also conduct an empirical study about the scalability of the MA, effectiveness of the hybridization technique and selection of crossover operator in the MA.

Impact and interest:

1 citations in Scopus
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ID Code: 78381
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Memetic algorithm, heuristic algorithm, CORS placement, NRTK, combinatorial optimization
DOI: 10.1109/TCYB.2014.2367499
ISSN: 2168-2275
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTER SOFTWARE (080300) > Computer Software not elsewhere classified (080399)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 IEEE
Copyright Statement: Personal use is permitted, but republication/redistribution requires IEEE permission.
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Deposited On: 03 Nov 2014 23:10
Last Modified: 02 Oct 2015 06:51

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