Articles

Pareto-based multi-objective node placement of industrial wireless sensor networks using binary differential evolution harmony search

  • Ling Wang ,
  • Lu An ,
  • Hao-Qi Ni ,
  • Wei Ye ,
  • Panos M. Pardalos ,
  • Min-Rui Fei
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  • 1 Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;
    2 Department of Industrial and Systems Engineering, Center for Applied Optimization, University of Florida, Gainesville, Florida 32611, USA

Received date: 2014-04-08

  Revised date: 2016-01-28

  Online published: 2016-02-24

Supported by

This work is supported by the National Natural Science Foundation of China (Grant Nos. 61304031,61304143), the Innovation Program of Shanghai Municipal Education Commission (Grant No. 14YZ007), the Key Project of Science and Technology Commission of Shanghai Municipality (Grant Nos. 14JC1402200, 14DZ1206302), the Key Project of Shanghai Municipal Commission of Economy and Informatization, and the Research Foundation for the Doctoral Program of Higher Education of China (Grant No. 20103108120008).

Abstract

The reliability and real time of industrial wireless sensor networks (IWSNs) are the absolute requirements for industrial systems, which are two foremost obstacles for the large-scale applications of IWSNs. This paper studies the multi-objective node placement problem to guarantee the reliability and real time of IWSNs from the perspective of systems. A novel multi-objective node deployment model is proposed in which the reliability, real time, costs and scalability of IWSNs are addressed. Considering that the optimal node placement is an NP-hard problem, a new multi-objective binary differential evolution harmony search (MOBDEHS) is developed to tackle it, which is inspired by the mechanism of harmony search and differential evolution. Three large-scale node deployment problems are generated as the benCHmarks to verify the proposed model and algorithm. The experimental results demonstrate that the developed model is valid and can be used to design large-scale IWSNs with guaranteed reliability and real-time performance efficiently. Moreover, the comparison results indicate that the proposed MOBDEHS is an effective tool for multi-objective node placement problems and superior to Pareto-based binary differential evolution algorithms, nondominated sorting genetic algorithm II (NSGA-II) and modified NSGA-II.

Cite this article

Ling Wang , Lu An , Hao-Qi Ni , Wei Ye , Panos M. Pardalos , Min-Rui Fei . Pareto-based multi-objective node placement of industrial wireless sensor networks using binary differential evolution harmony search[J]. Advances in Manufacturing, 2016 , 4(1) : 66 -78 . DOI: 10.1007/s40436-016-0135-8

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