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A Cooperative Coevolutionary Multiobjective Algorithm Using Non-dominated Sorting

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Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3102))

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Abstract

The following paper describes a cooperative coevolutionary algorithm which incorporates a novel collaboration formation mechanism. It encourages rewarding of components participating in successful collaborations from each sub-population. The successfulness of the collaboration is measured by a non-dominated sorting procedure. The algorithm has demonstrated it can perform comparably with the NSGA-II on some multiobjective function optimization problems.

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References

  1. Hillis, D.: Coevolving Parasites Improves Simulated Evolution as an Optimization Procedure. In: Langton, C.G., Taylor, C., Farmer, J.D., Rasmussen, S. (eds.) Artificial Life II - Proc. of the Workshop on the Synthesis and Simulation of Living Systems, pp. 313–324. Addison Wesley, Redwood City (1990)

    Google Scholar 

  2. Coello, C.A.C., Sierra, M.R.: A Coevolutionary Multi-objective Evolutionary Algorithm. In: Sarker, R., Reynolds, R., Abbass, H., Tan, K.C., McKay, B., Essam, D., Gedeon, T. (eds.) Proc. 2003 Congress on Evolutionary Computation (CEC 2003), pp. 482–489. IEEE Press, Piscataway (2003)

    Chapter  Google Scholar 

  3. Potter, M.A., De Jong, K.A.: Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents. Evolutionary Computation 8(1), 1–29 (2000)

    Article  Google Scholar 

  4. Eriksson, R., Olsson, B.: Cooperative Coevolution in Inventory Control Optimisation. In: Smith, G.D., Steele, N.C., Albrecht, R.F. (eds.) Proc. of the Third International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA 1997), pp. 583–587. Springer, Berlin (1997)

    Google Scholar 

  5. Potter, M.A., De Jong, K.A., Grefenstette, J.J.: A Coevolutionary Approach to Learning Sequential Decision Rules. In: Eshelman, L. (ed.) Proc. of the Sixth International Conference on Genetic Algorithms, pp. 366–372. Morgan Kaufmann, San Francisco (1995)

    Google Scholar 

  6. Tan, K.C., Yang, Y.J., Lee, T.H.: A Distributed Cooperative Coevolutionary Algorithm for Multiobjective Optimization. In: Sarker, R., Reynolds, R., Abbass, H., Tan, K.C., McKay, B., Essam, D., Gedeon, T. (eds.) Proc. 2003 Congress on Evolutionary Computation (CEC 2003), pp. 2513–2520. IEEE Press, Piscataway (2003)

    Chapter  Google Scholar 

  7. Keerativuttitumrong, N., Chaiyaratana, N., Varavithya, V.: Multi-objective Cooperative Coevolutionary Genetic Algorithm. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 288–297. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  8. Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the Strength Pareto Evolutionary Algorithm. In: Giannakoglou, K.C., Tsahalis, D.T., Periaux, J., Papailiou, K.D., Fogarty, T. (eds.) EUROGEN 2001, Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems, Barcelona Spain. International Center for Numerical Methods in Engineering (Cmine), pp. 95–100 (2001)

    Google Scholar 

  9. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II,”. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

    Article  Google Scholar 

  10. Fonsea, C.M., Fleming, P.J.: Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion, and Generalization. In: Forrest, S. (ed.) Proc. of the Fifth International Conference on Genetic Algorithms, vol. 26, pp. 30–45. Morgan Kaufmann, Los Altos (1993)

    Google Scholar 

  11. Potter, M.A., De Jong, K.: A Cooperative Coevolutionary Approach to Function Optimization. In: Proc. of Parallel Problem Solving From Nature III (PPSN III), pp. 249–257. Springer, Berlin (1995)

    Google Scholar 

  12. Mao, J., et al.: Genetic Symbiosis Algorithm for Multiobjective Optimization Problems. In: Beyer, H., et al. (eds.) Proc. 2001 Genetic and Evolutionary Computation Congress (GECCO 2001), p. 771. Morgan Kaufmann, San Francisco (2001)

    Google Scholar 

  13. Barbosa, H.J.C., Barreto, A.M.S.: An Interactive Genetic Algorithm with Co-evolution of Weights for Multiobjective Problems. In: Beyer, H., et al. (eds.) Proc. 2001 Genetic and Evolutionary Computation Congress (GECCO 2001)., pp. 203–210. Morgan Kaufmann, San Francisco (2001)

    Google Scholar 

  14. Parmee, I.C., Watson, A.H.: Preliminary Airframe Design Using Co-evolutionary Multiobjective Genetic Algorithms. In: Banzhaf, W., et al. (eds.) Proc. 1999 Genetic and Evolutionary Computation Congress (GECCO 1999), pp. 1657–1665. Morgan Kaufmann, San Francisco (1999)

    Google Scholar 

  15. Lohn, J., Kraus, W.F., Haith, G.L.: Comparing a Coevolutionary Genetic Algorithm for Multiobjective Optimization. In: Fogel, D., et al. (eds.) Proc. 2002 Congress on Evolutionary Computation (CEC 2002), pp. 1157–1162. IEEE Press, Piscataway (2002)

    Chapter  Google Scholar 

  16. Lohn, J., et al.: A Comparison of Dynamic Fitness Schedules for Evolutionary Design of Amplifiers. In: Stoica, A., Keymeulen, D., Lohn, J. (eds.) The First NASA/DoDWorkshop on Evolvable Hardware, pp. 87–92. IEEE Press, Los Alamitos (1999)

    Chapter  Google Scholar 

  17. Deb, K., Agrawal, R.B.: Simulated Binary Crossover for Continuous Search Space. Complex Systems 9(2), 115–148 (1995)

    MATH  MathSciNet  Google Scholar 

  18. Deb, K., Kumar, A.: Real-coded Genetic Algorithms with Simulated Binary Crossover: Studies on Multi-modal and Multi-objective Problems. Complex Systems 9(6), 431–454 (1995)

    Google Scholar 

  19. Deb, K., Goyal, M.: A Combined Genetic Adaptive Search (GENEAS) for Engineering Design. Computer Science and Informatics 26(4), 30–45 (1995)

    Google Scholar 

  20. Zitzler, E., Deb, K., Thiele, L.: Comparison of multiobjective evolutionary algorithms: Empirical results. Evolutionary Computation 8(2), 173–195 (2000)

    Article  Google Scholar 

  21. Salomon, R.: Re-evaluating Genetic Algorithm Performance Under Coordinate Rotation of Benchmark Functions: A Survey of Some Theoretical and Practical Aspects of Genetic Algorithms. Bio Systems 39(3), 263–278 (1996)

    Article  Google Scholar 

  22. Weicker, K., Weicker, N.: On the Improvement of Coevolutionary Optimizers by Learning Variable Interdependencies. In: Proc. 1999 Congress on Evolutionary Computation (CEC 1999), pp. 1627–1632. IEEE Press, Los Alamitos (1999)

    Google Scholar 

  23. Iorio, A.W., Li, X.: Parameter Control Within a Cooperative Coevolutionary Genetic Algorithm. In: Guervós, J.J.M., et al. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 247–256. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. School of Computer Science and Information Technology, Royal Melbourne Institute of Technology University, Melbourne, Vic, 3001, Australia

    Antony W. Iorio & Xiaodong Li

Authors
  1. Antony W. Iorio
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  2. Xiaodong Li
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Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), 208016, Kanpur, Uttar Pradesh, India

    Kalyanmoy Deb

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Iorio, A.W., Li, X. (2004). A Cooperative Coevolutionary Multiobjective Algorithm Using Non-dominated Sorting. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_56

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  • DOI: https://doi.org/10.1007/978-3-540-24854-5_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22344-3

  • Online ISBN: 978-3-540-24854-5

  • eBook Packages: Springer Book Archive

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