Differential evolution for the linear ordering problem implemented on CUDA

2011 IEEE Congress of Evolutionary Computation, CEC 2011

Volumn , Issue , 2011, Pages 796-802

  Krömer, Pavel ^a   Platoš, Jan ^a   Snášel, Vaclav ^a  

^a VSB TECHNICAL UNIVERSITY OF OSTRAVA   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

COMBINATORIAL OPTIMIZATION PROBLEMS; DIFFERENTIAL EVOLUTION; LINEAR ORDERINGS; NP-HARD PROBLEM; REAL-WORLD APPLICATION; TEST DATA;

COMBINATORIAL OPTIMIZATION; COMPUTATIONAL COMPLEXITY; SET THEORY;

EVOLUTIONARY ALGORITHMS;

EID: 80052006434     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2011.5949700     Document Type: Conference Paper

References (26)

1. H. T. Jongen, K. Meer, and E. Triesch, Optimization Theory. Kluwer Academic Publishers, 2004.
2. R. Martí and G. Reinelt, The Linear Ordering Problem - Exact and Heuristic Methods in Combinatorial Optimization, ser. Applied Mathematical Sciences. Springer Heidelberg Dordrecht London New York, 2011, vol. 175.
3. R. Martí, G. Reinelt, and A. Duarte, A benchmark library and a comparison of heuristic methods for the linear ordering problem, Computational Optimization and Applications, pp. 1-21, 2011.
4. T. Schiavinotto and T. Stützle, Search space analysis for the linear ordering problem, in Applications of Evolutionary Computing, ser. Lecture Notes in Computer Science, G. R. Raidl, J.-A. Meyer, M. Middendorf, S. Cagnoni, J. J. R. Cardalda, D. Corne, J. Gottlieb, A. Guillot, E. Hart, C. G. Johnson, and E. Marchiori, Eds., vol. 2611. Berlin, Germany: Springer-Verlag, 2003, pp. 322-333.
5. T. Schiavinotto and T. Stützle, The linear ordering problem: Instances, search space analysis and algorithms, Journal of Mathematical Modelling and Algorithms, vol. 3, no. 4, pp. 367-402, 2004. (Pubitemid 40317584)
6. V. Campos, F. Glover, M. Laguna, and R. Martí, An experimental evaluation of a scatter search for the linear ordering problem, J. of Global Optimization, vol. 21, no. 4, pp. 397-414, 2001. (Pubitemid 33672376)
7. G. Reinelt, The Linear Ordering Problem: Algorithms and Applications, ser. Research and Exposition in Mathematics. Heldermann Verlag Berlin, 1985, vol. 8.
8. J. E. Mitchell and B. Borchers, Solving linear ordering problems with a combined interior point/simplex cutting plane algorithm, Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, Tech. Rep., September 1997, accepted for publication in Proceedings of HPOPT97, Rotterdam, The Netherlands.
9. G. Huang and A. Lim, Designing a hybrid genetic algorithm for the linear ordering problem, in GECCO, 2003, pp. 1053-1064.
10. G. Hager, T. Zeiser, and G. Wellein, Data access optimizations for highly threaded multi-core cpus with multiple memory controllers, in Parallel and Distributed Processing, 2008. IPDPS 2008. IEEE International Symposium on, 2008, pp. 1-7.
11. M. Andrecut, Fast gpu implementation of sparse signal recovery from random projections, Engineering Letters, vol. 17, no. 3, pp. 151-158, 2009.
12. T. Preis, P. Virnau, W. Paul, and J. J. Schneider, Accelerated fluctuation analysis by graphic cards and complex pattern formation in Econophysics, New J. Phys., vol. 11, p. 093024, 2009.
13. D. Patnaik, S. P. Ponce, Y. Cao, and N. Ramakrishnan, Acceleratororiented algorithm transformation for temporal data mining, Network and Parallel Computing Workshops, IFIP International Conference on, vol. 0, pp. 93-100, 2009.
14. T. J. Desell, D. P. Anderson, M. Magdon-Ismail, H. J. Newberg, B. K. Szymanski, and C. A. Varela, An analysis of massively distributed evolutionary algorithms, in IEEE Congress on Evolutionary Computation. IEEE, 2010, pp. 1-8.
15. P. Pospíchal, J. Jaroš, and J. Schwarz, Parallel genetic algorithm on the cuda architecture, in Applications of Evolutionary Computation, ser. LNCS 6024. Springer Verlag, 2010, pp. 442-451.
16. D. Robilliard, V. Marion, and C. Fonlupt, High performance genetic programming on gpu, in Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems, ser. BADS'09. New York, NY, USA: ACM, 2009, pp. 85-94.
17. W. Langdon and W. Banzhaf, A simd interpreter for genetic programming on gpu graphics cards, in Genetic Programming, ser. Lecture Notes in Computer Science, M. O'Neill, L. Vanneschi, S. Gustafson, A. Esparcia Alcázar, I. De Falco, A. Della Cioppa, and E. Tarantino, Eds. Springer Berlin/Heidelberg, 2008, vol. 4971, pp. 73-85.
18. W. Zhu, Massively parallel differential evolution - pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems, Journal of Global Optimization, pp. 1-21.
19. L. de Veronese and R. Krohling, Differential evolution algorithm on the gpu with c-cuda, in Evolutionary Computation (CEC), 2010 IEEE Congress on, 2010, pp. 1-7.
20. W. Zhu and Y. Li, Gpu-accelerated differential evolutionary markov chain monte carlo method for multi-objective optimization over continuous space, in Proceeding of the 2nd workshop on Bio-inspired algorithms for distributed systems, ser. BADS'10. New York, NY, USA: ACM, 2010, pp. 1-8.
21. N. Fujimoto and S. Tsutsui, A highly-parallel tsp solver for a gpu computing platform, in Numerical Methods and Applications, ser. Lecture Notes in Computer Science, I. Dimov, S. Dimova, and N. Kolkovska, Eds. Springer Berlin/Heidelberg, 2011, vol. 6046, pp. 264-271.
22. NVIDIA, NVIDIA CUDA Programming Guide 3.2, 2010. [Online]. Available: http://developer.download.nvidia.com/compute/cuda/3 2 prod/toolkit/docs/CUDA C Programming Guide.pdf
23. K. V. Price, R. M. Storn, and J. A. Lampinen, Differential Evolution A Practical Approach to Global Optimization, ser. Natural Computing Series, G. Rozenberg, T. Bäck, A. E. Eiben, J. N. Kok, and H. P. Spaink, Eds. Berlin, Germany: Springer-Verlag, 2005.
24. NVIDIA, CUDA Toolkit 3.2 Math Library Performance, 2011. [Online]. Available: http://developer.download.nvidia.com/compute/cuda/3 2/docs/CUDA 3.2 Math Libraries Performance.pdf
25. D. Ashlock, Evolutionary computation for modeling and optimization. Springer, 2005.
26. V. Snášel, P. Krömer, and J. Platoš, Differential evolution and genetic algorithms for the linear ordering problem. in KES (1), ser. Lecture Notes in Computer Science, J. D. Velásquez, S. A. Ríos, R. J. Howlett, and L. C. Jain, Eds., vol. 5711. Springer, 2009, pp. 139-146.