Using Choquet integral as preference model in interactive evolutionary multiobjective optimization

European Journal of Operational Research

Volumn 250, Issue 3, 2016, Pages 884-901

  Branke, Juergen ^a   Corrente, Salvatore ^b   Greco, Salvatore ^b,c   Słowiński, Roman ^d,e   Zielniewicz, Piotr ^e  

^a UNIVERSITY OF WARWICK   (United Kingdom)

^b University of Catania and CESifo Research Network   (Italy)

^c UNIVERSITY OF PORTSMOUTH   (United Kingdom)

^d SYSTEMS RESEARCH INSTITUTE   (Poland)

^e POZNAN UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Choquet integral; Evolutionary algorithms; Interaction between criteria; Multiobjective optimization

Indexed keywords

ALGORITHMS; DECISION MAKING; ECONOMIC AND SOCIAL EFFECTS; EVOLUTIONARY ALGORITHMS; INTEGRAL EQUATIONS; OPTIMIZATION; PARETO PRINCIPLE;

CHOQUET INTEGRAL; EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION; EXPERIMENTAL ANALYSIS; INTERACTION BETWEEN CRITERION; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; PREFERENCE INFORMATION; PREFERENCE MODELING; VALUE FUNCTION MODEL;

MULTIOBJECTIVE OPTIMIZATION;

EID: 84951782805     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2015.10.027     Document Type: Article

References (45)

1. Angilella S., Corrente S., and Greco S. Stochastic multiobjective acceptability analysis for the Choquet integral preference model and the scale construction problem European Journal of Operational Research 240 1 2015 172 182
2. Angilella S., Greco S., Lamantia F., and Matarazzo B. Assessing non-additive utility for multicriteria decision aid European Journal of Operational Research 158 3 2004 734 744
3. Angilella S., Greco S., and Matarazzo B. Non-additive robust ordinal regression: a multiple criteria decision model based on the Choquet integral European Journal of Operational Research 201 1 2010 277 288
4. Battiti R., and Passerini A. Brain-computer evolutionary multiobjective optimization: a genetic algorithm adapting to the decision maker IEEE Transactions on Evolutionary Computation 14 5 2010 671 687
5. Branke J. Consideration of user preferences in evolutionary multi-objective optimization J. Branke, K. Deb, K. Miettinen, R. Słowiński, Multiobjective optimization - interactive and evolutionary approaches Lecture notes in computer series 5252 2008 Springer 157 178
6. Branke J. MCDA and multiobjective evolutionary algorithms S. Greco, M. Ehrgott, J. Figueira, Multiple criteria decision analysis: state of the art surveys 2nd ed. 2015 Springer
7. Branke J., Deb K., Miettinen K., and Słowiński R. Multiobjective optimization: interactive and evolutionary approaches 5252 2008 Springer
8. Branke J., Greco S., Słowiński R., and Zielniewicz P. Interactive evolutionary multiobjective optimization using robust ordinal regression M. Ehrgott, International conference on evolutionary multi-criterion optimization Lecture notes in computer series 5467 2009 Springer 554 568
9. Branke J., Greco S., Słowiński R., and Zielniewicz P. Interactive evolutionary multiobjective optimization driven by robust ordinal regression Bulletin of the Polish Academy of Sciences - Technical Sciences 58 3 2010 347 358
10. Branke J., Greco S., Słowiński R., and Zielniewicz P. Learning value functions in interactive evolutionary multiobjective optimization IEEE Transactions on Evolutionary Computation 19 1 2015 88 102
11. Branke J., Kaußler T., and Schmeck H. Guidance in evolutionary multi-objective optimization Advances in Engineering Software 32 2001 499 507
12. Campigotto P., and Passerini A. Adapting to a realistic decision maker: experiments towards a reactive multi-objective optimizer Proceedings of International conference on learning and intelligent optimization Lecture notes in computer series 6073 2010 Springer 338 341
13. Chateauneuf A., and Jaffray J. Some characterizations of lower probabilities and other monotone capacities through the use of Möbius inversion. Mathematical Social Sciences 17 1989 263 283
14. Choquet G. Theory of capacities Annales de l'institut Fourier 5 1954 131 295
15. Coello C.A.C. Handling preferences in evolutionary multiobjective optimization: a survey Congress on evolutionary computation 1 2000 IEEE 30 37
16. Coello C.C., Veldhuizen D.V., and Lamont G. Evolutionary algorithms for solving multi-objective problems 2002 Kluwer
17. Corrente S., Greco S., Kadziński M., and Słowiński R. Robust ordinal regression in preference learning and ranking Machine Learning 93 2 2013 381 422
18. Deb K., Agrawal S., Pratap A., and Meyarivan T. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II Proceedings of the sixth international conference on parallel problem solving from nature, PPSN VI 2000 Springer 849 858
19. Deb K., and Chaudhuri S. I-MODE: an interactive multi-objective optimization and decision-making using evolutionary methods Technical report KanGAL Report no. 2007003 2007 Indian Institute of Technology Kanpur
20. Deb K., Sinha A., Korhonen P., and Wallenius J. An interactive evolutionary multiobjective optimization method based on progressively approximated value functions IEEE Transactions on Evolutionary Computation 14 5 2010 723 739
21. Fonseca C.M., and Fleming P.J. Genetic algorithms for multiobjective optimization: Formulation, discussion, and generalization Proceedings of the fifth international conference on genetic algorithms 1993 416 423
22. Fowler J.W., Gel E.S., Köksalan M.M., Korhonen P., Marquis J.L., and Wallenius J. Interactive evolutionary multi-objective optimization for quasi-concave preference functions European Journal of Operational Research 206 2010 417 425
23. Grabisch M. The application of fuzzy integrals in multicriteria decision making European Journal of Operational Research 89 1996 445 456
24. Grabisch M. k-order additive discrete fuzzy measures and their representation Fuzzy Sets and Systems 92 1997 167 189
25. Grabisch M., and Labreuche C. Fuzzy measures and integrals in MCDA J. Figueira, S. Greco, M. Ehrgott, Multiple criteria decision analysis: state of the art surveys 2005 Springer Berlin 563 604
26. Grabisch M., Labreuche C., and Vansnick J.-C. On the extension of pseudo-boolean functions for the aggregation of interacting criteria European Journal of Operational Research 148 1 2003 28 47
27. Greco S., Mousseau V., and Słowiński R. Ordinal regression revisited: multiple criteria ranking using a set of additive value functions European Journal of Operational Research 191 2 2008 416 436
28. Greenwood G.W., Hu X.S., and D'Ambrosio J.G. Fitness functions for multiple objective optimization problems: combining preferences with Pareto rankings Foundations of genetic algorithms 1997 Morgan Kaufmann 437 455
29. Jaimes A.L., Montano A.A., and Coello C.A.C. Preference incorporation to solve many-ojective airfoil design problems Congress on evolutionary computation 2011 IEEE 1605 1612
30. Jaszkiewicz A. Interactive multiobjective optimization with the Pareto memetic algorithm Foundations of Computing and Decision Sciences 32 1 2007 15 32
31. Karahan I., and Köksalan M. A territory defining multiobjective evolutionary algorithms and preference incorporation IEEE Transactions on Evolutionary Computation 14 4 2010 636 664
32. Keeney R., and Raiffa H. Decisions with multiple objectives: preferences and value tradeoffs 1993 John Wiley & Sons New York
33. Knowles J. A summary-attainment-surface plotting method for visualizing the performance of stochastic multiobjective optimizers Intelligent systems design and applications, 2005. Isda'05. proceedings. 5th international conference on 2005 IEEE 552 557
34. Korhonen P., Wallenius J., and Zionts S. Solving the discrete multiple criteria problem using convex cones Management Science 30 1984 1336 1345
35. Marichal J., and Roubens M. Determination of weights of interacting criteria from a reference set European Journal of Operational Research 124 3 2000 641 650
36. Nelder J., and Mead R. A simplex method for function minimization The Computer Journal 7 4 1965 308 313
37. Phelps S., and Köksalan M. An interactive evolutionary metaheuristic for multiobjective combinatorial optimization Management Science 49 12 2003 1726 1738
38. Pirlot M., Schmitz H., and Meyer P. An empirical comparison of the expressiveness of the additive value function and the Choquet integral models for representing rankings Proceedings of the 25th Mini-EURO conference on uncertainty and robustness in planning and decision making, URPDM, Coimbra, Portugal 2010
39. Rachmawati L., and Srinivasan D. Preference incorporation in multi-objective evolutionary algorithms: a survey Congress on evolutionary computation 2006 IEEE 3385 3391
40. Rota G. On the foundations of combinatorial theory I. Theory of Möbius functions Wahrscheinlichkeitstheorie und Verwandte Gebiete 2 1964 340 368
41. Said L.B., Bechikh S., and Ghedira K. The r-dominance: a new dominance relation for interactive evolutionary multicriteria decision making IEEE Transactions on Evolutionary Computation 14 5 2010 801 818
42. Shafer G. A mathematical theory of evidence 1976 Princeton University Press
43. Thiele L., Miettinen K., Korhonen P.J., and Molina J. A preference-based interactive evolutionary algorithm for multiobjective optimization Evolutionary Computation Journal 17 3 2009 411 436
44. Todd D.S., and Sen P. Directed multiple objective search of design spaces using genetic algorithms and neural networks W. Banzhaf, Proceedings of Genetic and evolutionary computation conference 1999 Morgan Kaufmann San Francisco, California 1738 1743
45. Wagner T., and Trautmann H. Integration of preferences in hypervolume-based multiobjective evolutionary algorithms by means of desirability functions IEEE Transactions on Evolutionary Computation 14 5 2010 688 701