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The Dynamic Allocated Bees Algorithms for Multi-objective Problem

  • Lee, Ji-Young (Cardiff University, Manufacturing Engineering) ;
  • Oh, Jin-Seok (Korea Maritime University, Dept, of Mechatronics)
  • Published : 2009.05.31

Abstract

The aim of this research is to develop the Bees Algorithm named 'the dynamic allocated Bees Algorithm' for multi-objective problem, especially in order to be suit for Pareto optimality. In addition two new neighbourhood search methods have been developed to produce enhanced solutions for a multi-objective problem named 'random selection neighbourhood search' and 'weighted sum neighbourhood search' and they were compared with the basic neighbourhood search in the dynamic allocated Bees Algorithm. They were successfully applied to an Environmental/Economic (electric power) dispatch (EED) problem and simulation results presented for the standard IEEE 30-bus system and they were compared to those obtained using other approaches. The comparison shows the superiority of the proposed dynamic allocated Bees Algorithms and confirms its suitability for solving the multi-objective EED problem.

Keywords

References

  1. M.A. Abido, "A novel multi-objective evolutionary algorithm for environmental/economic power dispatch", Electric Power Systems Research, 65, pp. 71-81, 2003 https://doi.org/10.1016/S0378-7796(02)00221-3
  2. M.A. Abido, "A Niched Pareto genetic algorithm for multi-objective environmental/ economic powerdispatch", Electrical Power and Energy System, 25(2), pp. 97-105, 2003 https://doi.org/10.1016/S0142-0615(02)00027-3
  3. M.A. Abido, "Environmental/economic power dispatch using multiobjective evolutionary algorithms", IEEE Transactions on Power System, 18(4), 2003 https://doi.org/10.1109/TPWRS.2003.818693
  4. R.T.F.A. King, H.C.S. Rughooputh, and K. Deb, Evolutionary Multi-objective Environmental/Economic Dispatch:Stochastic Versus Deter-ministic Approaches Berlin Heidelberg, Springer - Verlag, 2005
  5. D.T. Pham, A. Ghanbarzadeh, E. Koc, S. Otri, S. Rahim and M. Zaidi, "The Bees algorithm - A novel tool for complex optimisation problems", Proc. 2nd I*PROMS Conf. on Intelligent Production Machines and Systems, pp. 454-459, 2006
  6. S. Camazine, J.L. Deneubourg, N.R. Franks, J. Sneyd, G. Theraulaz and E. Bonabeau, "Self-organization in Biological systems" Oxfordshire, Princeton University Press, 2001
  7. D.T. Pham and A. Ghanbarzadeh, "Multi-objective optimisation using the Bees Algorithm", Proc. 3nd I*PROMS Conference on Innovative Production Machines and Systems, 2007, pp. 529-533
  8. J.Y. Lee and A. Haj Darwish, "Multi-objective environmental/economic dispatch using the Bees algorithm with weighted sum", Proc. 1st EU-Korea Conf. on Science and Technology, pp. 267-274. 2008

Cited by

  1. Grouped Bees Algorithm: A Grouped Version of the Bees Algorithm vol.6, pp.1, 2017, https://doi.org/10.3390/computers6010005