77
Views
4
CrossRef citations to date
0
Altmetric
Articles

An Empirical Study of Aggregation Operators with Pareto Dominance in Multiobjective Genetic Algorithm

ORCID Icon, , , &

REFERENCES

  • K. Deb, Multi-Objective Optimization using Evolutionary Algorithms. New York: John Wiley & Sons, 2001.
  • N. Srinivas and K. Deb, “Multiobjective optimization using nondominated sorting in genetic algorithms,” J. Evol. Comput., Vol. 2, no. 3, pp. 221–48, 1994.
  • E. Zitzler and L. Thiele, “Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach,” Evol. Comput. IEEE Trans., Vol. 3, no. 4, pp. 257–71, 1999.
  • C. M. Fonseca and P. J. Fleming, “Genetic algorithms for multiobjective optimization: formulation, disscussion and generalization,” in 5th International Conference Genetic Algorithms, 1993, July, pp. 416–23.
  • K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Trans. Evol. Comput., Vol. 6, no. 2, pp. 182–97, 2002.
  • E. Zitzler, M. Laummanns, and L. Thiele, “SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization,” in Evolutionary Methods for Design, Optimization and Control, 2002, pp. 1–6.
  • B. Y. Qu and P. N. Suganthan, “Multi-objective evolutionary algorithms based on the summation of normalized objectives and diversified selection,” Inf. Sci. (Ny)., Vol. 180, no. 17, pp. 3170–81, 2010.
  • C. A. C. Coello, G. T. Pulido, and M. S. Lechuga, “Handling multiple objectives with particle swarm optimization,” Evol. Comput. IEEE Trans., Vol. 8, no. 3, pp. 256–79, 2004.
  • S.-Z. Zhao and P. N. Suganthan, “Multi-objective evolutionary algorithm with ensemble of external archives,” Int. J. Innov. Comput. Inf. Control, Vol. 6, no. 4, pp. 1713–1726, 2010.
  • P. Koduru, Z. D. Z. Dong, S. Das, S. M. Welch, J. L. Roe, and E. Charbit, “A multiobjective evolutionary-simplex hybrid approach for the optimization of differential equation models of gene networks,” IEEE Trans. Evol. Comput., Vol. 12, no. 5, pp. 572–90, 2008.
  • D. Kundu, K. Suresh, S. Ghosh, S. S. Das, B. K. Panigrahi, and S. S. Das, “Multi-objective optimization with artificial weed colonies,” Inf. Sci. (Ny)., Vol. 181, no. 12, pp. 2441–54, 2011.
  • M. Garza-Fabre, G. T. Pulido, and C. A. C. Coello, “Ranking methods for many-objective optimization,” in MICAI 2009: Advances in Artificial Intelligence, Vol. 5845, 2009, pp. 633–45.
  • H. Ishibuchi, T. Doi, and Y. Nojima, “Incorporation of scalarizing fitness functions into evolutionary multiobjective optimization algorithms,” in Parallel Problem Solving from Nature, Sep. 2006, pp. 493–502.
  • H. Ishibuchi, N. Tsukamoto, and Y. Nojima, “Empirical Analysis of using weighted sum fitness functions in NSGA-II for many-objective 0/1 Knapsack problems,” in UKSim 2009:11th International Conference on Computer Modelling and Simulation, 2009, pp. 71–6.
  • Z. He, G. G. Yen, and J. Zhang, “Fuzzy-based pareto optimality for many-objective evolutionary algorithms,” IEEE Trans. Evol. Comput., Vol. 18, no. 2, pp. 269–285, 2014.
  • K. Deep, K. P. Singh, M. L. Kansal, and C. Mohan, “An interactive method using genetic algorithm for multi-objective optimization problems modeled in fuzzy environment,” Expert Syst. Appl., Vol. 38, no. 3, pp. 1659–1667, 2011.
  • F. Y. Cheng and D. Li, “Multiobjective optimization of structures with and without control,” J. Guid. Control. Dyn., Vol. 19, no. 2, pp. 392–7, Mar. 1996.
  • A. Zhou, B.-Y. Qu, H. Li, S.-Z. Zhao, P. N. Suganthan, and Q. Zhang, “Multiobjective evolutionary algorithms: A survey of the state of the art,” Swarm Evol. Comput., Vol. 1, no. 1, pp. 32–49, 2011.
  • K. Deb, L. Thiele, M. Laumanns, and E. Zitzler, “Scalable Test Problems for Evolutionary Multiobjective Optimization,” in Evolutionary Multiobjective Optimization, no. 1990, A. Abraham, L. Jain, R. Goldberg, Eds. London: Springer-Verlag, 2005, 105–145.
  • M. Laumanns, L. Thiele, K. Deb, and E. Zitzler, “Combining convergence and diversity in evolutionary multiobjective optimization,” Evol. Comput., Vol. 10, no. 3, pp. 263–82, Sep. 2002.
  • J. D. Knowles and D. Corne, “Bounded Pareto archiving: Theory and practice,” in Metaheuristics for Multiobjective optimisation, X. Gandibleux, M. Sevaux, K. Sörensen, and V. T'kindt, Eds. Berlin Heidelberg: Springer, 2004, pp. 39–64.
  • M. Ojha, K. P. Singh, P. Chakraborty, and S. Verma, “An Aggregation Based Approach with Pareto Ranking in Multiobjective Genetic Algorithm,” in Proceedings of Fifth International Conference on Soft Computing for Problem Solving, SocProS 2015, 2016, vol. 437, pp. 261–271.
  • X. Zhang, Y. Tian, R. Cheng, and Y. Jin, “An efficient approach to non-dominated sorting for evolutionary multi-objective optimization,” IEEE Trans. Evol. Comput., Vol. 19, no. 2, pp. 201–213, 2015.
  • Q. Zhang, A. Zhou, S. Zhao, P. N. Suganthan, W. Liu, and S. Tiwari, “Multiobjective optimization test instances for the CEC 2009 special session and competition,” Univ. Essex, Colchester, UK, Nanyang Technol. Univ., Singapore, Tech. Rep. CES-487, 2009.
  • J. R. Schott, “Fault tolerant design using single and multicriteria genetic algorithm optimization,” M.S. thesis, Aeronaut. Astronaut., Mass. Inst. Technol., Cambridge, MA, 1995.
  • R. T. Marler and J. S. Arora, “Survey of multi-objective optimization methods for engineering,” Struct. Multidiscip. Optim., Vol. 26, no. 6, pp. 369–95, 2004.
  • L. J. Eshelman and J. D. Schaffer, “Real-coded genetic algorithms and interval-schemata,” in Foundations of Genetic Algorithms II, L. D. Whitley, Ed. San Mateo, CA: Morgan Kaufmann, 1993, pp. 187–202.
  • K. Deb and A. Kumar, “Real-coded genetic algorithms with simulated binary crossover: Studies on multi-modal and multi-objective problems.,” Complex Syst., Vol. 9, no. 6, pp. 431–54, 1995.
  • K. Deb and H. Jain, “An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, part i: solving problems with box constraints,” IEEE Trans. Evol. Comput., Vol. 18, no. 4, pp. 577–601, 2014.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.