Particle swarm optimization with Monte-Carlo simulation and hypothesis testing for network reliability problem

Lu Yao Wu, Wei Neng Chen, Hao Hui Deng, Jun Zhang, Yun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

Abstract

The performance of Monte-Carlo Simulation(MCS) is highly related to the number of simulation. This paper introduces a hypothesis testing technique and incorporated into a Particle Swarm Optimization(PSO) based Monte-Carlo Simulation(MCS) algorithm to solve the complex network reliability problem. The function of hypothesis testing technique is to reduce the dispensable simulation in network system reliability estimation. The proposed technique contains three components: hypothesis testing, network reliability calculation and PSO algorithm for finding solutions. The function of hypothesis testing is to abandon unpromising solutions; we use monte-carlo simulation to obtain network reliability; since the network reliability problem is NP-hard, PSO algorithm is applied. Since the execution time can be better decreased with the decrease of Confidence level of hypothesis testing in a range, but the solution becomes worse when the confidence level exceed a critical value, the experiment are carried out on different confidence levels for finding the critical value. The experimental results show that the proposed method can reduce the computational cost without any loss of its performance under a certain confidence level.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Advanced Computational Intelligence, ICACI 2016
Pages310-317
Number of pages8
DOIs
Publication statusPublished - 7 Apr 2016
Event8th International Conference on Advanced Computational Intelligence, ICACI 2016 - Chiang Mai, Thailand
Duration: 14 Feb 201616 Feb 2016

Conference

Conference8th International Conference on Advanced Computational Intelligence, ICACI 2016
CountryThailand
CityChiang Mai
Period14/02/1616/02/16

Keywords

  • hypothesis testing
  • Monte-Carlo simulation
  • network reliability
  • network reliability optimization
  • particle swarm optimization

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