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We present a dynamic algorithm for solving the Longest Common SubsequenceProblem using Ant Colony Optimization Technique. The Ant Colony OptimizationTechnique has been applied to solve many problems in Optimization Theory,Machine Learning and Telecommunication Networks etc. In particular, applicationof this theory in NP-Hard Problems has a remarkable significance. Given twostrings, the traditional technique for finding Longest Common Subsequence isbased on Dynamic Programming which consists of creating a recurrence relationand filling a table of size . The proposed algorithm draws analogy withbehavior of ant colonies function and this new computational paradigm is knownas Ant System. It is a viable new approach to Stochastic CombinatorialOptimization. The main characteristics of this model are positive feedback,distributed computation, and the use of constructive greedy heuristic. Positivefeedback accounts for rapid discovery of good solutions, distributedcomputation avoids premature convergence and greedy heuristic helps findacceptable solutions in minimum number of stages. We apply the proposedmethodology to Longest Common Subsequence Problem and give the simulationresults. The effectiveness of this approach is demonstrated by efficientComputational Complexity. To the best of our knowledge, this is the first AntColony Optimization Algorithm for Longest Common Subsequence Problem.

A Dynamic Algorithm for the Longest Common Subsequence Problem using Ant Colony Optimization Technique