A Collaborative Approach for LA-DHBMO

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.

[1]  H A Abbass,et al.  MARRIAGE IN HONEY-BEE OPTIMIZATION (MBO): A HAPLOMETROSIS POLYGYNOUS SWARMING APPROACH , 2001 .

[2]  Magdalene Marinaki,et al.  A honey bees mating optimization algorithm for the open vehicle routing problem , 2011, GECCO '11.

[3]  Vahid Azadehgan,et al.  A New Hybrid Algorithm for Multiobjective Optimization , 2011, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence.

[4]  Xin‐She Yang,et al.  Appendix A: Test Problems in Optimization , 2010 .

[5]  Hussein A. Abbass,et al.  MBO: marriage in honey bees optimization-a Haplometrosis polygynous swarming approach , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[6]  Hussein A. Abbass,et al.  A Monogenous MBO Approach to Satisfiability , 2001 .

[7]  Barry J. Adams,et al.  Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation , 2007, J. Frankl. Inst..

[8]  Dervis Karaboga,et al.  A survey: algorithms simulating bee swarm intelligence , 2009, Artificial Intelligence Review.

[9]  Ali Maroosi,et al.  Application of honey-bee mating optimization algorithm on clustering , 2007, Appl. Math. Comput..

[10]  Xin-She Yang Test Problems in Optimization , 2010, 1008.0549.

[11]  P. S. Sastry,et al.  Varieties of learning automata: an overview , 2002, IEEE Trans. Syst. Man Cybern. Part B.

[12]  Kumpati S. Narendra,et al.  Learning automata - an introduction , 1989 .

[14]  Xin-She Yang,et al.  Engineering Optimization: An Introduction with Metaheuristic Applications , 2010 .