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A genetic algorithm for solving fuzzy shortest path problems with mixed fuzzy arc lengths

Hassanzadeh, R ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1016/j.mcm.2011.03.040
  3. Publisher: 2013
  4. Abstract:
  5. We are concerned with the design of a model and an algorithm for computing the shortest path in a network having various types of fuzzy arc lengths. First, a new technique is devised for the addition of various fuzzy numbers in a path using α-cuts by proposing a least squares model to obtain membership functions for the considered additions. Due to the complexity of the addition of various fuzzy numbers for larger problems, a genetic algorithm is presented for finding the shortest path in the network. For this, we apply a recently proposed distance function for comparison of fuzzy numbers. Examples are worked out to illustrate the applicability of the proposed approach
  6. Keywords:
  7. A-cut ; Genetic algorithm ; Arc length ; Distance functions ; Fuzzy numbers ; Least Square ; Regression model ; Shortest path ; Shortest path problem ; Fuzzy rules ; Graph theory ; Regression analysis ; Genetic algorithms
  8. Source: Mathematical and Computer Modelling ; Volume 57, Issue 1-2 , January , 2013 , Pages 84-99 ; 08957177 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0895717711002007