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An Efficient Two-Phase Ant Colony Optimization Algorithm for the Closest String Problem

  • Hoang Xuan Huan
  • Dong Do Duc
  • Nguyen Manh Ha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7673)

Abstract

Given a finite set S of strings of length m, the task of finding a string t that minimizes the Hamming distance from t to S, has wide applications. This paper presents a two-phase Ant Colony Optimization (ACO) algorithm for the problem. The first phase uses the Smooth Max-Min (SMMAS) rule to update pheromone trails. The second phase is a memetic algorithm that uses ACO method to generate a population of solutions in each iteration, and a local search technique on the two best solutions. The efficiency of our algorithm has been evaluated by comparing to the Ant-CSP algorithm.

Keywords

Memetic algorithm Ant Colony Optimization Closest String Problem Local Search Pheromone update rule 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hoang Xuan Huan
    • 1
  • Dong Do Duc
    • 1
  • Nguyen Manh Ha
    • 1
  1. 1.University of Engineering and Technology, VNUHanoiVietnam

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