Automatic design of evolutionary algorithms for multi-objective combinatorial optimization

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8672, Issue , 2014, Pages 508-517

  Bezerra, Leonardo C T ^a   López Ibáñez, Manuel ^a   Stützle, Thomas ^a  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

COMBINATORIAL OPTIMIZATION; DESIGN; OPTIMIZATION; PROBLEM SOLVING;

AUTOMATIC DESIGN; DESIGN METHODOLOGY; FLEXIBLE FRAMEWORK; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; MULTI-OBJECTIVE METAHEURISTICS; MULTIOBJECTIVE COMBINATORIAL OPTIMIZATION; PERMUTATION FLOW SHOPS; RESEARCH EFFORTS;

EVOLUTIONARY ALGORITHMS;

EID: 84921771915     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10762-2_50     Document Type: Article

References (24)

1. Bader, J., Zitzler, E.: HypE: An algorithm for fast hypervolume-based manyobjective optimization. Evolutionary Computation 19(1), 45-76 (2011).
2. Beume, N., Naujoks, B., Emmerich, M.: SMS-EMOA: Multiobjective selection based on dominated hypervolume. Eur. J. Oper. Res. 181(3), 1653-1669 (2007).
3. Bezerra, L. C. T., López-Ibáñez, M., Stützle, T.: Automatic generation of multiobjective ACO algorithms for the biobjective knapsack problem. In: Dorigo, M., Birattari, M., Blum, C., Christensen, A. L., Engelbrecht, A. P., Groß, R., Stützle, T. (eds.) ANTS 2012. LNCS, vol. 7461, pp. 37-48. Springer, Heidelberg (2012).
4. Bezerra, L. C. T., López-Ibáñez, M., Stützle, T.: Automatic design of evolutionary algorithms for multi-objective combinatorial optimization: Supplementary material (2014), http://iridia. ulb. ac. be/supp/IridiaSupp2014-007/.
5. Bezerra, L. C. T., López-Ibáñez, M., Stützle, T.: Deconstructing multi-objective evolutionary algorithms: An iterative analysis on the permutation flowshop. In: Pardalos, P., et al. (eds.) LION 8. LNCS. Springer (2014).
6. Biscani, F., Izzo, D., Yam, C. H.: A global optimisation toolbox for massively parallel engineering optimisation (2010), http://arxiv. org/abs/1004. 3824.
7. Bleuler, S., Laumanns, M., Thiele, L., Zitzler, E.: PISA-a platform and programming language independent interface for search algorithms. In: Fonseca, C. M., Fleming, P. J., Zitzler, E., Deb, K., Thiele, L. (eds.) EMO 2003. LNCS, vol. 2632, pp. 494-508. Springer, Heidelberg (2003).
8. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 181-197 (2002).
9. Dubois-Lacoste, J., López-Ibáñez, M., Stützle, T.: A hybrid TP+PLS algorithm for bi-objective flow-shop scheduling problems. Comput. Oper. Res. 38(8), 1219-1236 (2011).
10. Fonseca, C. M., Fleming, P. J.: Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In: Forrest, S. (ed.) ICGA, pp. 416-423. Morgan Kaufmann Publishers (1993).
11. Igel, C., Heidrich-Meisner, V., Glasmachers, T.: Shark. Journal of Machine Learning Research 9, 993-996 (2008).
12. Knowles, J. D., Corne, D.: Approximating the nondominated front using the Pareto archived evolution strategy. Evolutionary Computation 8(2), 149-172 (2000).
13. Liefooghe, A., Jourdan, L., Talbi, E. G.: A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEOMOEO. Eur. J. Oper. Res. 209(2), 104-112 (2011).
14. López-Ibáñez, M., Dubois-Lacoste, J., Stützle, T., Birattari, M.: The irace package, iterated race for automatic algorithm configuration. Tech. Rep. TR/IRIDIA/2011-004, IRIDIA, Université Libre de Bruxelles, Belgium (2011).
15. López-Ibáñez, M., Knowles, J., Laumanns, M.: On sequential online archiving of objective vectors. In: Takahashi, R. H. C., Deb, K., Wanner, E. F., Greco, S. (eds.) EMO 2011. LNCS, vol. 6576, pp. 46-60. Springer, Heidelberg (2011).
16. López-Ibáñez, M., Stützle, T.: The automatic design of multi-objective ant colony optimization algorithms. IEEE Trans. Evol. Comput. 16(6), 861-875 (2012).
17. Minella, G., Ruiz, R., Ciavotta, M.: A review and evaluation of multiobjective algorithms for the flowshop scheduling problem. INFORMS Journal on Computing 20(3), 451-471 (2008).
18. Taillard, É. D.: Benchmarks for basic scheduling problems. Eur. J. Oper. Res. 64(2), 278-285 (1993).
19. Van Veldhuizen, D. A., Lamont, G. B.: Multiobjective evolutionary algorithms: Analyzing the state-of-the-art. Evolutionary Computation 8(2), 125-147 (2000).
20. Zhang, Q., Suganthan, P. N.: Special session on performance assessment of multiobjective optimization algorithms/CEC 2009 MOEA competition (2009).
21. Zitzler, E., Künzli, S.: Indicator-based selection in multiobjective search. In: Yao, X., et al. (eds.) PPSN VIII. LNCS, vol. 3242, pp. 832-842. Springer, Heidelberg (2004).
22. Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization. In: Giannakoglou, K. C., et al. (eds.) EUROGEN 2001, pp. 95-100. CIMNE, Barcelona (2002).
23. Zitzler, E., Thiele, L., Bader, J.: On set-based multiobjective optimization. IEEE Trans. Evol. Comput. 14(1), 58-79 (2010).
24. Zitzler, E., Thiele, L., Deb, K.: Comparison of multiobjective evolutionary algorithms: Empirical results. Evolutionary Computation 8(2), 173-195 (2000).