A hybrid variable neighborhood search and simulated annealing algorithm to estimate the three parameters of the Weibull distribution

  • Authors:

  • Babak Abbasi;Seyed Taghi Akhavan Niaki;Mehrzad Abdi Khalife;Yasser Faize

  • Affiliations:

  • Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran;Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran;Department of Industrial Engineering, Qazvin Islamic Azad University, Qazvin, Iran;Department of Industrial Engineering, Qazvin Islamic Azad University, Qazvin, Iran

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

The Weibull distribution plays an important role in failure distribution modeling of reliability research. While there are three parameters in the general form of this distribution, for simplicity, one of its parameters is usually omitted and as a result, the others are estimated easily. However, due to its more flexibility, when the general form of the Weibull distribution is of interest, the estimation procedure is not an easy task anymore. For example, in the maximum likelihood estimation method, the likelihood function that is formed for a three-parameter Weibull distribution is very hard to maximize. In this paper, a new hybrid methodology based on a variable neighborhood search and a simulated annealing approach is proposed to maximize the likelihood function of a three-parameter Weibull distribution. The performance of the proposed methodology in terms of both the estimation accuracy and the required CPU time is then evaluated and compared to the ones of an existing current method through a wide range of numerical examples in which a sensitivity analysis is performed on the sample size. The results of the comparison study show that while the proposed method provides accurate estimates as well as those of the existing method, it requires significantly less CPU time.