A Multiobjective Evolutionary Algorithm Based on Decision Variable Analyses for Multiobjective Optimization Problems with Large-Scale Variables

IEEE Transactions on Evolutionary Computation

Volumn 20, Issue 2, 2016, Pages 275-298

  Ma, Xiaoliang ^a   Liu, Fang ^a   Qi, Yutao ^a   Wang, Xiaodong ^a   Li, Lingling ^a   Jiao, Licheng ^a   Yin, Minglei ^a   Gong, Maoguo ^a  

^a XIDIAN UNIVERSITY   (China)

Author keywords

cooperative co evolution; Interacting variables; problem decomposition

Indexed keywords

ALGORITHMS; DECISION MAKING; EVOLUTIONARY ALGORITHMS; OPTIMIZATION; PROBLEM SOLVING;

COOPERATIVE CO-EVOLUTION; HIGH-DIMENSIONAL PROBLEMS; INTERACTING VARIABLES; MULTI-OBJECTIVE OPTIMIZATION PROBLEM; MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION PROBLEMS (MOPS); PROBLEM DECOMPOSITION; SINGLE OBJECTIVE OPTIMIZATION;

MULTIOBJECTIVE OPTIMIZATION;

EID: 84963808596     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TEVC.2015.2455812     Document Type: Article

References (60)

1. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms. New York, NY, USA: Wiley, 2001.
2. Q. Zhang and H. Li, "MOEA/D: A multi-objective evolutionary algorithm based on decomposition," IEEE Trans. Evol. Comput., vol. 11, no. 6, pp. 712-731, Dec. 2007.
3. N. Beume, B. Naujoks, and M. Emmerich, "SMS-EMOA: Multiobjective selection based on dominated hypervolume," Eur. J. Oper. Res., vol. 181, no. 3, pp. 1653-1669, 2007.
4. 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, Aug. 2014.
5. T. Weise, R. Chiong, and K. Tang, "Evolutionary optimization: Pitfalls and booby traps," J. Comput. Sci. Technol., vol. 27, no. 5, pp. 907-936, 2012.
6. M. Potter and K. Jong, "A cooperative coevolutionary approach to function optimization," in Proc. Int. Conf. Parallel Probl. Solv. Nat., vol. 2. Jerusalem, Israel, 1994, pp. 249-257.
7. Z. Yang, K. Tang, and X. Yao, "Large scale evolutionary optimization using cooperative coevolution," Inf. Sci., vol. 178, no. 15, pp. 2985-2999, 2008.
8. X. Li and X. Yao, "Cooperatively coevolving particle swarms for large scale optimization," IEEE Trans. Evol. Comput., vol. 16, no. 2, pp. 210-224, Apr. 2012.
9. Y. Mei, X. Li, and X. Yao, "Cooperative co-evolution with route distance grouping for large-scale capacitated arc routing problems," IEEE Trans. Evol. Comput., vol. 18, no. 3, pp. 435-449, Jun. 2014.
10. D. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA, USA: Addison-Wesley, 1989.
11. Y. Chen, T. Yu, K. Sastry, and D. Goldberg, "A survey of linkage learning techniques in genetic and evolutionary algorithms," Illinois Genet. Algorithms Libr., Univ. Illinois Urbana-Champaign, Urbana, IL, USA, Tech. Rep. 2007014, 2007.
12. S. Huband, P. Hingston, L. Barone, and L. While, "A review of multiobjective test problems and a scalable test problem toolkit," IEEE Trans. Evol. Comput., vol. 10, no. 5, pp. 477-506, Oct. 2006.
13. Q. Zhang et al., "Multiobjective optimization test instances for the CEC 2009 special session and competition," School Comput. Sci. Electr. Eng., Univ. Essex, Colchester, U.K., Tech. Rep. CES-887, 2008.
14. Q. Zhang, A. Zhou, and Y. Jin, "RM-MEDA: A regularity model-based multiobjective estimation of distribution algorithm," IEEE Trans. Evol. Comput., vol. 12, no. 1, pp. 41-63, Feb. 2008.
15. L. Jiao, Y. Li, M. Gong, and X. Zhang, "Quantum-inspired immune clonal algorithm for global optimization," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 38, no. 5, pp. 1234-1253, Oct. 2008.
16. K. Tang, X. Li, P. Suganthan, Z. Yang, and T. Weise, "Benchmark functions for the CEC'2010 special session and competition on large-scale global optimization," Nat. Inspir. Comput. Appl. Lab., Univ. Sci. Technol. China, Hefei, China, Tech. Rep. 2010001, 2010.
17. T. Yu, D. Goldberg, K. Sastry, C. Lima, and M. Pelikan, "Dependency structure matrix, genetic algorithms, and effective recombination," Evol. Comput., vol. 17, no. 4, pp. 595-626, 2009.
18. W. Chen, T. Weise, Z. Yang, and K. Tang, "Large-scale global optimization using cooperative coevolution with variable interaction learning," in Proc. Conf. Parallel Probl. Solv. Nat., Kraków, Poland, 2010, pp. 300-309.
19. P. Toint, "Test problems for partially separable optimization and results for the routine PSPMIN," Dept. Math., Univ. Namur, Namur, Belgium, Tech. Rep. 83/4, 1983.
20. B. Colson and P. Toint, "Optimizing partially separable functions without derivatives," Optim. Methods Softw., vol. 20, nos. 4-5, pp. 493-508, 2005.
21. M. Omidvar, X. Li, Y. Mei, and X. Yao, "Cooperative co-evolution with differential grouping for large scale optimization," IEEE Trans. Evol. Comput., vol. 18, no. 3, pp. 378-393, Jun. 2014.
22. D. Thierens and D. Goldberg, "Mixing in genetic algorithms," in Proc. 5th Int. Conf. Genet. Algorithms, Urbana, IL, USA, 1993, pp. 38-45.
23. M. Munetomo and D. Goldberg, "Identifying linkage groups by nonlinearity/ nonmonotonicity detection," in Proc. Genet. Evol. Comput. Conf., vol. 1. Orlando, FL, USA, 1999, pp. 433-440.
24. M. Tezuka, M. Munetomo, and K. Akama, "Linkage identification by nonlinearity check for real-coded genetic algorithms," in Proc. Genet. Evol. Comput. Conf., Seattle, WA, USA, 2004, pp. 222-233.
25. K. Weicker and N. Weicker, "On the improvement of coevolutionary optimizers by learning variable interdependencies," in Proc. IEEE Congr. Evol. Comput., Washington, DC, USA, 1999, pp. 1627-1632.
26. Y. Chen, "Extending the scalability of linkage learning genetic algorithms: Theory and practice," Ph.D. dissertation, Dept. Comput. Sci., Univ. Illinois Urbana-Champaign, Urbana, IL, USA, 2004.
27. J. E. Smith, "Self adaptation in evolutionary algorithms," Ph.D. dissertation, Dept. Comput. Sci., Univ. West England, Bristol, U.K., 1998.
28. Q. Zhang and H. Muehlenbein, "On the convergence of a class of estimation of distribution algorithms," IEEE Trans. Evol. Comput., vol. 8, no. 2, pp. 127-136, Apr. 2004.
29. G. R. Harik, F. G. Lobo, and D. E. Goldberg, "The compact genetic algorithm," IEEE Trans. Evol. Comput., vol. 3, no. 4, pp. 287-297, Nov. 1999.
30. M. Pelikan and D. Goldberg, "BOA: The Bayesian optimization algorithm," in Proc. Genet. Evol. Comput. Conf., Orlando, FL, USA, 1999, pp. 525-532.
31. T. Yu, A. Yassine, and D. Goldberg, "A genetic algorithm for developing modular product architectures," in Proc. ASME Int. Design Eng. Tech. Conf., Chicago, IL, USA, 2003, pp. 515-524.
32. K. Miettinen, Nonlinear Multiobjective Optimization. Boston, MA, USA: Kluwer Academic, 1999.
33. C. Hillermeier, Nonlinear Multiobjective Optimization - A Generalized Homotopy Approach. Boston, MA, USA: Birkhauser, 2001.
34. E. Zitzler, K. Deb, and L. Thiele, "Comparison of multiobjective evolutionary algorithms: Empirical results," Evol. Comput., vol. 8, no. 2, pp. 173-195, 2000.
35. K. Deb, L. Thiele, M. Laumanns, and E. Zitzler, "Scalable multiobjective optimization test problems," in Proc. Congr. Evol. Comput., Honolulu, HI, USA, 2002, pp. 825-830.
36. H. Liu, F. Gu, and Q. Zhang, "Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems," IEEE Trans. Evol. Comput., vol. 18, no. 3, pp. 450-455, Jun. 2014.
37. K. Fang and D. Lin, "Uniform designs and their application in industry," in Handbook on Statistics in Industry, vol. 22. Amsterdam, The Netherlands: Elsevier, 2003, pp. 131-170.
38. M. Omidvar, X. Li, and X. Yao, "Smart use of computational resources based on contribution for cooperative co-evolutionary algorithms," in Proc. Genet. Evol. Comput. Conf., Dublin, Ireland, 2011, pp. 1115-1122.
39. R. Storn and K. Price, "Differential evolution - A simple and efficient heuristic for global optimization over continuous spaces," J. Global Optim., vol. 11, no. 4, pp. 341-359, 1997.
40. K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE Trans. Evol. Comput., vol. 6, no. 2, pp. 182-197, Apr. 2002.
41. L. Tseng and C. Chen, "Multiple trajectory search for unconstrained/ constrained multi-objective optimization," in Proc. IEEE Congr. Evol. Comput., Trondheim, Norway, 2009, pp. 1951-1958.
42. P. Bosman and D. Thierens, "The naive MIDEA: A baseline multi-objective EA," in Proc. Evol. Multi-Criterion Optim. (EMO), Guanajuato, Mexico, 2005, pp. 428-442.
43. C. Ahn, "Advances in evolutionary algorithms," in Theory, Design and Practice. Berlin, Germany: Springer, 2006.
44. Q. Zhang, W. Liu, and H. Li, "The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances," School Comput. Sci. Electr. Eng., Univ. Essex, Colchester, U.K., Tech. Rep. 20091, 2009.
45. M. Liu, X. Zou, Y. Chen, and Z. Wu, "Performance assessment of DMOEA-DD with CEC 2009 MOEA competition test instances," in Proc. IEEE Congr. Evol. Comput., Trondheim, Norway, 2009, pp. 2913-2918.
46. E. Zitzler, L. Thiele, M. Laumanns, C. Fonseca, and V. Fonseca, "Performance assessment of multiobjective optimizers: An analysis and review," IEEE Trans. Evol. Comput., vol. 7, no. 2, pp. 117-132, Apr. 2003.
47. J. Derrac, S. Garca, D. Molina, and F. Herrera, "A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms," Swarm Evol. Comput., vol. 1, no. 1, pp. 3-18, 2011.
48. J. Durillo et al., "A study of multiobjective metaheuristics when solving parameter scalable problems," IEEE Trans. Evol. Comput., vol. 14, no. 4, pp. 618-635, Aug. 2010.
49. L. Marti, J. Garcia, A. Berlanga, and J. Molina, "Introducing MONEDA: Scalable multiobjective optimization with a neural estimation of distribution algorithm," in Proc. Genet. Evol. Comput. Conf. (GECCO), Atlanta, GA, USA, 2008, pp. 689-696.
50. L. Marti, J. Garcia, A. Berianga, and J. Molina, "Multi-objective optimization with an adaptive resonance theory-based estimation of distribution algorithm," Ann. Math. Artif. Intell., vol. 68, no. 4, pp. 247-273, 2013.
51. H. Wang, L. Jiao, R. Shang, S. He, and F. Liu, "A memetic optimization strategy based on dimension reduction in decision space," Evol. Comput., vol. 23, no. 1, pp. 69-100, 2015.
52. C.-K. Goh and K. C. Tan, "A competitive-cooperative coevolutionary paradigm for dynamic multi-objective optimization," IEEE Trans. Evol. Comput., vol. 13, no. 1, pp. 103-127, Feb. 2009.
53. Y. Qi, F. Liu, M. Liu, M. Gong, and L. Jiao, "Multi-objective immune algorithm with Baldwinian learning," Appl. Soft Comput., vol. 12, no. 8, pp. 2654-2674, 2012.
54. J. He, T. Chen, and X. Yao, "On the easiest and hardest fitness functions," IEEE Trans. Evol. Comput., vol. 19, no. 2, pp. 295-305, Apr. 2015.
55. G. Karafotias, M. Hoogendoorn, and A. Eiben, "Parameter control in evolutionary algorithms: Trends and challenges," IEEE Trans. Evol. Comput., vol. 19, no. 2, pp. 167-187, Apr. 2015.
56. W. Song, Y. Wang, H. Li, and Z. Cai, "Locating multiple optimal solutions of nonlinear equation systems based on multiobjective optimization," IEEE Trans. Evol. Comput., vol. 19, no. 3, pp. 414-431, Jun. 2015.
57. T. Tusar and B. Filipic, "Visualization of Pareto front approximations in evolutionary multiobjective optimization: A critical review and the prosection method," IEEE Trans. Evol. Comput., vol. 19, no. 2, pp. 225-245, Apr. 2015.
58. M. Asafuddoula, T. Ray, and R. Sarker, "A decomposition-based evolutionary algorithm for many objective optimization," IEEE Trans. Evol. Comput., vol. 19, no. 3, pp. 445-460, Jun. 2015.
59. H. Wang, L. Jiao, and X. Yao, "Two-Arch2: An improved two-archive algorithm for many-objective optimization," IEEE Trans. Evol. Comput., vol. 19, no. 4, pp. 103-127, 2015.
60. S. Bandyopadhyay and A. Mukherjee, "An algorithm for many-objective optimization with reduced objective computations: A study in differential evolution," IEEE Trans. Evol. Comput., vol. 19, no. 3, pp. 400-413, Jun. 2015.