Author(s)

Vahid Azadehgan, Payam Khanteimouri, Sorayya Akbari, Niusha Ghandehari

Department of Information Technology, Sufi Razi Institute of Higher Education, Zanjan, Iran.
Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

Honey Bees Mating Optimization (HBMO) is a novel developed method used in different engineering areas. Optimiza-tion process in this algorithm is inspired of natural mating behavior between bees. In this paper, we have attempted to createa new collaborative learning automata based honey bees mating optimization (C-LA-DHBMO).In previous model presented by very authors, the same learning automata parameters for all drones were used. However in the presented method, learning automatas with different reward and penalty parameters have been used which enhance reliability of algorithm and also has high convergence speed compared to previous proposed algorithm (LA-DHBMO). Simulation and comparisons based on several well-studied benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed algorithms.

Honey Bees Mating Optimization; Learning Automata; Collaborative Optimization; Function Optimization

V. Azadehgan, P. Khanteimouri, S. Akbari and N. Ghandehari, "A Collaborative Approach for LA-DHBMO," Applied Mathematics, Vol. 3 No. 10A, 2012, pp. 1442-1447. doi: 10.4236/am.2012.330203.