Exchange strategies for multiple Ant Colony System

  • Authors:

  • Issmail Ellabib;Paul Calamai;Otman Basir

  • Affiliations:

  • Department of Systems Design Engineering, University of Waterloo, Waterloo, Ont., Canada N2L 3G1;Department of Systems Design Engineering, University of Waterloo, Waterloo, Ont., Canada N2L 3G1;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ont., Canada N2L 3G1

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2007

Quantified Score

Hi-index 0.08

Visualization

Abstract

In this paper we apply the concept of parallel processing to enhance the performance of the Ant Colony System algorithm. New exchange strategies based on a weighting scheme are introduced under three different types of interactions. A search assessment technique based on a team consensus methodology is developed to study the influence of these strategies on the search behavior. This technique demonstrates the influence of these strategies in terms of search diversity. The performance of the Multiple Ant Colony System algorithm, applied to the Vehicle Routing Problem with Time Windows as well as the Traveling Salesman Problem, is investigated and evaluated with respect to solution quality and computational effort. The experimental studies demonstrate that the Multiple Ant Colony System outperforms the sequential Ant Colony System. The studies also indicate that the weighting scheme improves performance, particularly in strategies that share pheromone information among all colonies. A considerable improvement is also obtained by combining the Multiple Ant Colony System with a local search procedure.