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Intuitionistic Fuzzy Estimation of the Ant Colony Optimization Starting Points

  • Stefka Fidanova
  • Krassimir Atanassov
  • Pencho Marinov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7116)

Abstract

The ability of ant colonies to form paths for carrying food is rather fascinating. The problem is solved collectively by the whole colony. This ability is explained by the fact that ants communicate in an indirect way by laying trails of pheromone. The higher the pheromone trail within a particular direction, the higher the probability of choosing this direction. The collective problem solving mechanism has given rise to a metaheuristic referred to as Ant Colony Optimization. On this work we use intoitionistic fuzzy estimation of start nodes with respect to the quality of the solution. Various start strategies are offered. Sensitivity analysis of the algorithm behavior according to estimation parameters is made. As a test problem Multidimensional (Multiple) Knapsack Problem is used.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefka Fidanova
    • 1
  • Krassimir Atanassov
    • 2
  • Pencho Marinov
    • 1
  1. 1.IICTBulgarian Academy of SciencesSofiaBulgaria
  2. 2.CLBMEBulgarian Academy of ScienceSofiaBulgaria

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