John Wiley & Sons, Chichester “Multi-Objective Optimization using Evolutionary Algorithms”, UK, 2001, ISBN 0-471-87339-X.
 C. M. Fonseca and P. J. Fleming, “Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization,” in Proceedings of the Fifth International Conference on Genetic Algorithms, S. Forrest, Ed. San Mateo, CA: Morgan Kauffman, pp. 416–423, 1993.
 N. Srinivas and K. Deb, “Multiobjective function optimization using nondominated sorting genetic algorithms,” Evol. Comput., Vol. 2, No. 3, pp. 221–248, Fall 1995.
 J. Horn, N. Nafploitis, and D. E. Goldberg, “ A niched Pareto genetic algorithm for multiobjective optimization,” in Proceedings of the First IEEE Conference on Evolutionary Computation, Z. Michalewicz, Ed. Piscataway, NJ: IEEE Press, pp. 82–87, 1994.
 Schaffer. Multiple Objective Optimization with Vector Evaluated Genetic Algorithms. Unpublished Ph.D. thesis, Vanderbilt University, Nashville, Tennessee, 1984.
 K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Trans. Evol. Comput., Vol. 6, pp. 182–197, Apr. 2002.
 E. Zitzler and L. Thiele. Multiobjective evolutionary algorithms: "A comparative case study and the strength pareto approach", IEEE Transactions on Evolutionary Computation, pp.257–271, 1999.
 E. Zitzler, M. Laumanns, and L. Thiele, “SPEA2: Improving the strength Pareto evolutionary algorithm,” in Proc. EUROGEN 2001. Evolutionary Methods for Design, Optimization and Control With Applications to Industrial Problems,K. Giannakoglou, D. Tsahalis, J. Periaux, P. Papailou, and T. Fogarty, Eds., Athens, Greece, Sept. 2001.J.
 J. Durillo, J. Garca, A. Nebro, C. Coello, F. Luna, and E. Alba, “Multi-objective particle swarm optimizers: An experimental comparison”, 5th International Conference on Evolutionary MultiCriterion Optimization (EMO2009), 2009.
 C. Garca, O. Cordn, and F. Herrera, “An empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria ts”, ANTS Workshop, pp. 61–72, 2004.
 D. Simon, “Biogeography-based optimization”, IEEE Trans. on Evolutionary Computation. Vol. 12, No. 6, pp.702-713, 2008.
 M. Ergezer, D. Simon, D. Du, “Oppositional biogeographybased optimization”, In Proceedings of the IEEE Conferencon Systems, Man, and Cybernetics, IEEE, San Antonio,TX, USA, pp. 1035-1040, 2009.
 D. Du, D. Simon, M. Ergezer, "Biogeography-based optimization combined with evolutionary strategy and immigration refusal", In Proceedings of the IEEE Conference on Systems, Man, and Cybernetics,IEEE, San Antonio, TX,USA, pp. 1023-1028, 2009.
 H. Ma, S. Ni, M. Sun, " Equilibrium species counts and migration model tradeos for biogeography-based optimization", In Proceedings of the 48th IEEE Conference on Decision and Control, IEEE, Shanghai, China, pp. 3306-3310, 2009.
 N. Johal, S. Singh, and H. Kundra, " A hybrid FPAB/BBO algorithm for satellite image classification", International Journal of Computer Applications, Vol. 6, No. 5, pp. 31-36, September 2010.
 Hai-Ping Ma,Xie-Yong Ruan ,Zhang-Xin Pan , "Handling Multiple Objectives with Biogeography-based Optimization,International Journal of Automation and Computing Vol. 9, No. 1, pp. 30-36, 2012.
 K. Jamuna and K. Swarup, "Multi-objective biogeography based optimization for optimal PMU placement", Applied Soft Computing, Vol. 12, No. 5, pp. 1503-1510, May 2012.
 M. Costa e Silva, L. Coelho, and L. Lebensztajn, "Multiobjective biogeography-based optimization based on predator-prey approach", IEEE Transactions on Magnetics, Vol. 48, 2, pp. 951-954, February 2012.
 Storn R, Price K, "Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces", JGlobal Opt, Vol. 11, No. 4, pp. 341–359.
 E. Zitzler, “Evolutionary algorithms for multiobjective optimization: Methods and application", Doctoral dissertation ETH 13398, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, 1999.
 H.-M. Voigt, W. Ebeling, I. Rechenberg, and H.-P. Schwefel, Eds. Berlin, “On the performance assessment and comparison of stochastic multiobjective optimizers,” in Parallel Problem Solving from NatureIV, Germany, Springer-Verlag, pp. 584–593, 1996.
 E. Zitzler, K. Deb, and L. Thiele, “Comparison of multiobjective evolutionary algorithms: Empirical results,” Evol. Comput. Vol. 8, No. 2, pp.173–195, summer 2000.
 J. Knowles and D. Corne, “The Pareto archived evolution strategy: Anew baseline algorithm for multiobjective optimization,” in Proceedings of the 1999 Congress on Evolutionary Computation. Piscataway, NJ: IEEE Press, pp. 98–105, 1999.
 Nateri Kaul Madavan, “Multi-objective optimization using a Pareto differential evolution approach” Proceeding of the Congress on Evolutionary Computation”, Vol.2, pp.862-869, 2003.
 Feng Xue, Arthur Cobut Sanderson, “Pareto-based multi-objective differential evolution”, Proceedings of the 2003 Congress on Evolutionary Computation, pp.420-431, 2003.
 Tea Rolic, Bogdan Filipic, “DEMO: Differential Evolution for Multi-objective Optimization”, Lecture Notes in Computer Science Vol. 34, No. 10, pp. 520-533, 2005.
 Guolin Yu, "An Improved Differential Evolution Algorithm for Multi-objective Optimization Problems", IJACT: International Journal of Advancements in Computing Technology, Vol. 3, No. 9, pp. 106 - 113, 2011.