A Study of Some Properties of Ant-Q
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem
INFORMS Journal on Computing
An Ant Colony System Hybridized with Randomized Algorithm for TSP
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Data mining with an ant colony optimization algorithm
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Domain information based prediction of protein-protein interactions of glucosinolate biosynthesis
International Journal of Computer Applications in Technology
A genetic ant colony algorithm for routing in CPS heterogeneous network
International Journal of Computer Applications in Technology
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In this paper, a hybrid optimisation algorithm for the motif detection problem of biological sequences is presented. Our method is improved Gibbs sampling method by employing an improved ant colony optimisation (ACO) algorithm. The goal of our method is to reduce the required computing time and get better solution. First, we find a set of better candidate positions for revising the motif by using an improved ACO. Then we use these candidate positions as the input to the Gibbs sampling method. The simulation results show that by employing our improved algorithm, both efficiency and quality for detecting motifs are improved compared with simple Gibbs sampling method.