Brain-computer evolutionary multiobjective optimization: A genetic algorithm adapting to the decision maker

IEEE Transactions on Evolutionary Computation

Volumn 14, Issue 5, 2010, Pages 671-687

  Battiti, Roberto ^a   Passerini, Andrea ^a  

^a UNIVERSITY OF TRENTO   (Italy)

Author keywords

Interactive decision making; machine learning; reactive search optimization; support vector ranking

Indexed keywords

BENCH-MARK PROBLEMS; CROSS VALIDATION; DECISION MAKERS; EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION; INCREMENTAL MODELS; INTEGRAL PART; INTERACTIVE DECISION MAKING; INTERACTIVE MULTIOBJECTIVE OPTIMIZATION; MACHINE-LEARNING; MULTIPLE CRITERIA DECISION MAKING; ONLINE MACHINES; OPTIMIZATION SCHEME; REACTIVE SEARCH; REACTIVE SEARCH OPTIMIZATION; SATISFICING; SELFTUNING; SOLUTION TECHNIQUES; SUPPORT VECTOR; SUPPORT VECTOR RANKING; TRAINING PROCEDURES; UTILITY FUNCTIONS;

DECISION MAKING; GENETIC ALGORITHMS; HUMAN COMPUTER INTERACTION; KNOWLEDGE MANAGEMENT; LEARNING SYSTEMS;

MULTIOBJECTIVE OPTIMIZATION;

EID: 77957552435     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TEVC.2010.2058118     Document Type: Article

References (56)

1. J. D. Schaffer, "Multiple objective optimization with vector evaluated genetic algorithms," in Proc. 1st Int. Conf. Genet. Algorithms, 1985, pp. 93-100.
2. N. Srinivas and K. Deb, "Multiobjective optimization using nondominated sorting in genetic algorithms," Evol. Computat., vol.2, no.3, pp. 221-248, Fall 1994.
3. E. Zitzler and L. Thiele, "Multiobjective evolutionary algorithms: A comparative case study and the strength pareto approach," IEEE Trans. Evol. Computat., vol.3, no.4, pp. 257-271, Nov. 1999.
4. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms. New York: Wiley, Jul. 2001, p. 518.
5. P. Bosman and D. Thierens, "The balance between proximity and diversity in multiobjective evolutionary algorithms," IEEE Trans. Evol. Computat., vol.7, no.2, pp. 174-188, Apr. 2003.
6. J. Branke, "Consideration of partial user preferences in evolutionary multiobjective optimization," in Multiobjective Optimization: Interactive and Evolutionary Approaches. Berlin/Heidelberg, Germany: Springer-Verlag, 2008, pp. 157-178.
7. F. di Pierro, K. Soon-Thiam, and D. Savic, "An investigation on preference order ranking scheme for multiobjective evolutionary optimization," IEEE Trans. Evol. Computat., vol.11, no.1, pp. 17-45, Feb. 2007.
8. I. Das, "A preference ordering among various Pareto optimal alternatives," Struct. Multidisciplinary Optimizat., vol.18, no.1, pp. 30-35, 1999.
9. J. March, "Bounded rationality, ambiguity, and the engineering of choice," Bell J. Econ., vol.9, no.2, pp. 587-608, 1978.
10. K. Miettinen, F. Ruiz, and A. Wierzbicki, "Introduction to multiobjective optimization: Interactive approaches," in Multiobjective Optimization: Interactive and Evolutionary Approaches. Berlin/Heidelberg, Germany: Springer-Verlag, 2008, pp. 27-57.
11. R. Battiti, M. Brunato, and F. Mascia, Reactive Search and Intelligent Optimization (Operations Research/Computer Science Interfaces Series 45). New York, NY: Springer-Verlag, 2008.
12. L. Citi, R. Poli, C. Cinel, and F. Sepulveda, "P300-based BCI mouse with genetically-optimized analogue control," IEEE Trans. Neural Syst. Rehabilitat. Engineer., vol.16, no.1, pp. 51-61, Feb. 2008.
13. D. Jones, "A taxonomy of global optimization methods based on response surfaces," J. Global Optimiz., vol.21, no.4, pp. 345-383, 2001.
14. Q. Zhang and H. Li, "MOEA/D: A multiobjective evolutionary algorithm based on decomposition," IEEE Trans. Evol. Computat., vol.11, no.6, pp. 712-731, Dec. 2007. (Pubitemid 350187486)
15. A.J. Branke, K. Deb, K. Miettinen, and R. Slowínski, Eds., Multiobjective Optimization: Interactive and Evolutionary Approaches. Berlin/Heidelberg, Germany: Springer-Verlag, 2008.
16. H. Takagi, "Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation," in Proc. IEEE, vol.89, no.9, pp. 1275-1296, Sep. 2001.
17. B. Roy and V. Mousseau, "A theoretical framework for analysing the notion of relative importance of criteria," J. Multicriteria Decision Anal., vol.5, no.2, pp. 145-159, 1996.
18. R. Steuer, Multiple Criteria Optimization: Theory, Computation, and Application. New York: Wiley, 1986.
19. L. Tanner, "Selecting a text-processing system as a qualitative multiple criteria problem," Eur. J. Oper. Res., vol.50, no.2, pp. 179-187, Jan. 1991.
20. V. V. Podinovskii, "The quantitative importance of criteria with discrete first-order metric scale," Autom. Remote Control, vol.65, no.8, pp. 1348-1354, 2004.
21. R. Steuer and E. Choo, "An interactive weighted Tchebycheff procedure for multiple objective programming," Math. Program., vol.26, no.3, pp. 326-344, 1983.
22. R. Dell and M. Karwan, "An interactive MCDM weight space reduction method utilizing a Tchebycheff utility function," Naval Res. Logistics, vol.37, no.2, pp. 263-277, 1990.
23. C. Cortes and V. N. Vapnik, "Support vector networks," Mach. Learn., vol.20, no.3, pp. 1-25, Sep. 1995.
24. S. Menchetti, "Learning preference and structured data: Theory and applications," Ph.D. dissertation, Dipartimento di Sistemi e Informatica, Universit́a Degli Studi di Firenze, Firenze, Italy, 2005.
25. W. W. Cohen, R. E. Schapire, and Y. Singer, "Learning to order things," J. Artificial Intell. Res., vol.10, no.1, pp. 243-270, Jan. 1999.
26. M. Collins and N. Duffy, "Convolution kernels for natural language," in Advances in Neural Information Processing Systems 14. Cambridge, MA: MIT Press, 2001, pp. 625-632.
27. M. Collins, N. Duffy, and F. Park, "New ranking algorithms for parsing and tagging: Kernels over discrete structures, and the voted perceptron," in Proc. ACL, 2002, pp. 263-270.
28. C. A. Micchelli, Y. Xu, and H. Zhang, "Universal kernels," J. Mach. Learn. Res., vol.7, pp. 2651-2667, Dec. 2006.
29. J. Shawe-Taylor and N. Cristianini, Kernel Methods for Pattern Analysis. New York: Cambridge Univ. Press, 2004.
30. S. Martello and P. Toth, Knapsack Problems: Algorithms and Computer Implementations. New York: Wiley, 1990.
31. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, "A fast elitist multiobjective genetic algorithm: NSGA-II," IEEE Trans. Evol. Computat., vol.6, no.2, pp. 182-197, Apr. 2002.
32. C. Burges, "A tutorial on support vector machines for pattern recognition," in Data Mining and Knowledge Discovery, vol.2. Boston, MA: Kluwer, 1998.
33. B. Settles, "Active learning literature survey," Univ. Wisconsin-Madison, Madison, WI, Tech. Rep. 1648, 2009.
34. F. Hutter, H. H. Hoos, K. Leyton-Brown, and T. Sẗutzle, "ParamILS: An automatic algorithm configuration framework," J. Artificial Intell. Res., vol.36, no.1, pp. 267-306, Sep. 2009.
35. C. Coello, "Handling preferences in evolutionary multiobjective optimization: A survey," in Proc. Congr. Evol. Computat., vol.1. 2000, pp. 30-37.
36. A. Jaszkiewicz and J. Branke, "Interactive multiobjective evolutionary algorithms," in Multiobjective Optimization: Interactive and Evolutionary Approaches. Berlin/Heidelberg, Germany: Springer-Verlag, 2008, pp. 179-193.
37. M. Sun, A. Stam, and R. Steuer, "Solving multiple objective programming problems using feed-forward artificial neural networks: The interactive FFANN procedure," Manage. Sci., vol.42, no.6, pp. 835-849, Jun. 1996.
38. M. Sun, A. Stam, and R. Steuer, "Interactive multiple objective programming using Tchebycheff programs and artificial neural networks," Comput. Oper. Res., vol.27, nos. 7-8, pp. 601-620, Jun. 2000.
39. H. Z. Huang, Z. G. Tian, and M. J. Zuo, "Intelligent interactive multiobjective optimization method and its application to reliability optimization," IIE Trans., vol.37, no.11, pp. 983-993, Nov. 2005.
40. T. Saaty, "Axiomatic foundation of the analytic hierarchy process," Manage. Sci., vol.32, no.7, pp. 841-855, 1986.
41. G. Quan, G. Greenwood, D. Liu, and S. Hu, "Searching for multiobjective preventive maintenance schedules: Combining preferences with evolutionary algorithms," Eur. J. Oper. Res., vol.177, no.3, pp. 1969-1984, 2007.
42. C. White, A. Sage, and A. Dozono, "A model of multiattribute decisionmaking and trade-off weight determination under uncertainty," IEEE Trans. Syst., Man, and Cybern., vol.14, no.2, pp. 223-229, 1984.
43. J. Figueira, S. Greco, V. Mousseau, and R. S?owínski, "Interactive multiobjective optimization using a set of additive value functions," in Lecture Notes in Computer Science. Berlin/Heidelberg, Germany: Springer-Verlag, 2008, pp. 97-119.
44. S. Phelps and M. Koksalan, "An interactive evolutionary metaheuristic for multiobjective combinatorial optimization," Manage. Sci., vol.49, no.12, pp. 1726-1738, Dec. 2003.
45. M. Koksalan, M. Karwan, and S. Zionts, "An improved method for solving multiple criteria problems involving discrete alternatives," IEEE Trans. Syst., Man, and Cybern., vol.14, no.1, pp. 24-34, 1984.
46. K. Deb, L. Thiele, M. Laumanns, and E. Zitzler, "Scalable multiobjective optimization test problems," in Proc. CEC, 2002, pp. 825-830.
47. D. Angluin, "Queries and concept learning," Mach. Learn., vol.2, no.4, pp. 319-342, 1988.
48. Y. Bengio, J. Louradour, R. Collobert, and J. Weston, "Curriculum learning," in Proc. 26th Int. Conf. Mach. Learn., 2009, pp. 41-48.
49. Y. Bengio and Y. LeCun, "Scaling learning algorithms toward AI," in Large-Scale Kernel Machines. Cambridge, MA: MIT Press, 2007.
50. Y. Abu-Mostafa, "Learning from hints," J. Complexity, vol.10, no.1, pp. 165-178, Mar. 1994.
51. D. Braziunas and C. Boutilier, "Minimax regret based elicitation of generalized additive utilities," in Proc. 23rd Conf. UAI, 2007, pp. 25-32.
52. M. Burl and E. Wang, "Active learning for directed exploration of complex systems," in Proc. 26th Int. Conf. Mach. Learn., 2009, pp. 89-96.
53. T. G̈artner, "Kernels for structured data," Ph.D. dissertation, Dept. Comput. Sci., Universiẗat Bonn, Bonn, Germany, 2005.
54. R. Caruana, "Multitask learning," Mach. Learn., vol.28, no.1, pp. 41-75, 1997.
55. T. Evgeniou, C. A. Micchelli, and M. Pontil, "Learning multiple tasks with kernel methods," J. Mach. Learn. Res., vol.6, pp. 615-637, Dec. 2005.
56. P. Campigotto and A. Passerini, "Adapting to a realistic decision maker: Experiments toward a reactive multiobjective optimizer," in Lecture Notes in Computer Science, vol.6073. Berlin/Heidelberg, Germany: Springer-Verlag, Jan. 2010, pp. 338-341.