W. Hongjian, Z. Naiyu, C. Jean-charles, M. Julien, and R. Yassine, Parallel Structured Mesh Generation with Disparity Maps by GPU Implementation, IEEE Transactions on Visualization & Computer Graphics, vol.21, issue.9, pp.1045-1057, 2015.

[. Bibliography, . Andre, R. John, and . Koza, Parallel genetic programming: A scalable implementation using the transputer network architecture, Advances in genetic programming, pp.317-337, 1996.

A. Achanta, K. Shaji, A. Smith, P. Lucchi, S. Fua et al., Slic superpixels compared to state-of-the-art superpixel methods. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.34, issue.11, pp.2274-2282, 2012.

[. Alba and M. Tomassini, Parallelism and evolutionary algorithms, IEEE Transactions on Evolutionary Computation, vol.6, issue.5, pp.443-462, 2002.
DOI : 10.1109/TEVC.2002.800880

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.64.430

T. Stephen and . Barnard, Stochastic stereo matching over scale, International Journal of Computer Vision, vol.3, issue.1, pp.17-32, 1989.

[. Bengoetxea, Inexact Graph Matching Using Estimation of Distribution Algorithms, Ecole Nationale Supérieure des Télécommunications, 2002.

J. Besag, Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986.
DOI : 10.1016/0031-3203(83)90012-2

Y. Boykov and V. Kolmogorov, An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.26, issue.9, pp.1124-1137, 2004.

I. Boussa¨?dboussa¨?d, J. Lepagnot, and P. Siarry, A survey on optimization metaheuristics, Information Sciences, vol.237, pp.82-117, 2013.
DOI : 10.1016/j.ins.2013.02.041

D. Bai, X. Ouyang, L. Li, H. He, and . Yu, Maxmin ant system on gpu with cuda, Innovative Computing, Information and Control Fourth International Conference on, pp.801-804, 2009.

S. Baker, D. Scharstein, S. Lewis, . Roth, J. Michael et al., A Database and Evaluation Methodology for Optical Flow, International Journal of Computer Vision, vol.27, issue.3, pp.1-31, 2011.
DOI : 10.1007/s11263-010-0390-2

E. Bienenstock, C. Von, and . Malsburg, A Neural Network for Invariant Pattern Recognition, Europhysics Letters (EPL), vol.4, issue.1, p.121, 1987.
DOI : 10.1209/0295-5075/4/1/020

Y. Boykov, O. Veksler, and R. Zabih, Markov random fields with efficient approximations, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231), pp.648-655, 1998.
DOI : 10.1109/CVPR.1998.698673

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.3857

Y. Boykov, O. Veksler, and R. Zabih, Fast approximate energy minimization via graph cuts. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.23, issue.11, pp.1222-1239, 2001.

J. L. Bentley, W. Bruce, . Weide, C. Andrew, and . Yao, Optimal Expected-Time Algorithms for Closest Point Problems, ACM Transactions on Mathematical Software, vol.6, issue.4, pp.563-580, 1980.
DOI : 10.1145/355921.355927

E. Cochrane and J. Beasley, The co-adaptive neural network approach to the Euclidean Travelling Salesman Problem, Neural Networks, vol.16, issue.10, pp.1499-1525, 2003.
DOI : 10.1016/S0893-6080(03)00056-X

J. Créput, A. Hajjam, A. Koukam, and O. Kuhn, Self-organizing maps in population based metaheuristic to the dynamic vehicle routing problem, Journal of Combinatorial Optimization, vol.23, issue.4, pp.437-458, 2012.
DOI : 10.1007/s10878-011-9400-8

P. James, . Cohoon, U. Shailesh, . Hegde, N. Worthy et al., Punctuated equilibria: a parallel genetic algorithm, Genetic algorithms and their applications: proceedings of the second International Conference on Genetic Algorithms at the Massachusetts Institute of Technology: L. Erlhaum Associates, 1987.

H. Cjl-+-13-]-zhuoyuan-chen, Z. Jin, S. Lin, Y. Cohen, and . Wu, Large displacement optical flow from nearest neighbor fields, Computer Vision and Pattern Recognition, 2013 IEEE Conference on, pp.2443-2450

J. Créput and A. Koukam, A memetic neural network for the Euclidean traveling salesman problem, Neurocomputing, vol.72, issue.4-6, pp.1250-1264, 2009.
DOI : 10.1016/j.neucom.2008.01.023

S. Tibério, . Caetano, J. Julian, L. Mcauley, . Cheng et al., Learning graph matching. Pattern Analysis and Machine Intelligence, IEEE Transactions on, issue.6, pp.311048-1058, 2009.

T. Cour, P. Srinivasan, and J. Shi, Balanced graph matching, Advances in Neural Information Processing Systems, vol.19, p.313, 2007.

T. Gabriel, C. , and M. Toulouse, Parallel strategies for metaheuristics, 2003.

T. Gabriel, C. , and M. Toulouse, Parallel meta-heuristics, Handbook of metaheuristics, pp.497-541, 2010.

M. Dorigo, Optimization, Learning and Natural Algorithms, 1992.

R. Durbin and D. Willshaw, An analogue approach to the travelling salesman problem using an elastic net method, Nature, vol.326, issue.6114, pp.689-691, 1987.
DOI : 10.1038/326689a0

L. Ford and D. R. Fulkerson, Flows in networks, volume 1962, 1962.

F. Pedro, . Felzenszwalb, P. Daniel, and . Huttenlocher, Efficient belief propagation for early vision, International Journal of Computer Vision, vol.70, issue.1, pp.41-54, 2006.

A. Alex, . Freitas, H. Simon, and . Lavington, Data parallelism, control parallelism, and related issues, Mining Very Large Databases with Parallel Processing, pp.71-78, 2000.

J. Michael and . Flynn, Some computer organizations and their effectiveness. Computers, IEEE Transactions on, vol.100, issue.9, pp.948-960, 1972.

G. Folino, C. Pizzuti, and G. Spezzano, A scalable cellular implementation of parallel genetic programming, IEEE Transactions on Evolutionary Computation, vol.7, issue.1, pp.37-53, 2003.
DOI : 10.1109/TEVC.2002.806168

S. Geman and D. Geman, Stochastic relaxation, gibbs distributions, and the bayesian restoration of images. Pattern Analysis and Machine Intelligence, IEEE Transactions on, issue.6, pp.721-741, 1984.

F. Güney and A. Geiger, Displets: Resolving stereo ambiguities using object knowledge, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.4165-4175, 2015.
DOI : 10.1109/CVPR.2015.7299044

K. Hartelius and J. M. Carstensen, Bayesian grid matching. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.25, issue.2, pp.162-173, 2003.
DOI : 10.1109/tpami.2003.1177149

P. Hansen and N. Mladenovi´cmladenovi´c, Variable neighborhood search: Principles and applications, European Journal of Operational Research, vol.130, issue.3, pp.449-467, 2001.
DOI : 10.1016/S0377-2217(00)00100-4

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.93.1769

C. Hosni, M. Rhemann, C. Bleyer, M. Rother, and . Gelautz, Fast cost-volume filtering for visual correspondence and beyond. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.35, issue.2, pp.504-511, 2013.

K. Berthold, . Horn, G. Brian, and . Schunck, Determining optical flow, Technical symposium east, pp.319-331, 1981.

S. David, . Johnson, A. Lyle, and . Mcgeoch, Experimental analysis of heuristics for the stsp, The traveling salesman problem and its variations, pp.369-443, 2007.

H. S. Tae-hyun-kim, K. Lee, and . Lee, Optical flow via locally adaptive fusion of complementary data costs, Computer Vision, 2013 IEEE International Conference on, pp.3344-3351, 2013.

T. Kohonen, Clustering, Taxonomy, and Topological Maps of Patterns, Sixth International Conference on, 1982.

Z. Konfrst, Parallel genetic algorithms: advances, computing trends, applications and perspectives, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings., p.162, 2004.
DOI : 10.1109/IPDPS.2004.1303155

R. Kennedy, J. Camillo, and . Taylor, Hierarchically-constrained optical flow, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3340-3348, 2015.
DOI : 10.1109/CVPR.2015.7298955

[. Kotropoulos, Frontal face authentication using morphological elastic graph matching, IEEE Transactions on Image Processing, vol.9, issue.4, pp.555-560, 2000.
DOI : 10.1109/83.841933

D. Keysers and W. Unger, Elastic image matching is NP-complete, Pattern Recognition Letters, vol.24, issue.1-3
DOI : 10.1016/S0167-8655(02)00268-4

S. Raymond, . Lee, N. James, and . Liu, Tropical cyclone identification and tracking system using integrated neural oscillatory elastic graph matching and hybrid rbf network track mining techniques, Neural Networks IEEE Transactions on, vol.11, issue.3, pp.680-689, 2000.

[. Lu, H. Yang, D. Min, N. Minh, and . Do, Patch Match Filter: Efficient Edge-Aware Filtering Meets Randomized Search for Fast Correspondence Field Estimation, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.1854-1861, 2013.
DOI : 10.1109/CVPR.2013.242

T. Malisiewicz and A. A. Efros, Improving Spatial Support for Objects via Multiple Segmentations, Procedings of the British Machine Vision Conference 2007, 2007.
DOI : 10.5244/C.21.55

M. Menze and A. Geiger, Object scene flow for autonomous vehicles, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3061-3070, 2015.
DOI : 10.1109/CVPR.2015.7298925

N. Mladenovi´cmladenovi´c and P. Hansen, Variable neighborhood search, Computers & Operations Research, vol.24, issue.11, pp.1097-1100, 1997.
DOI : 10.1016/S0305-0548(97)00031-2

. Middlebury, Middlebury Optical Flow Datasets, 2015.

. Middlebury, Middlebury Stereo Datasets, 2015.

N. Mladenovic, A variable neighborhood algorithm-a new metaheuristic for combinatorial optimization, papers presented at Optimization Days, p.112, 1995.

D. Marr and T. Poggio, Cooperative computation of stereo disparity, Science, vol.194, issue.4262, pp.283-287, 1976.
DOI : 10.1126/science.968482

B. Manderick and P. Spiessens, Fine-grained parallel genetic algorithms, Genetic algorithms Third International Conference on, pp.428-433, 1989.

S. Mcconnell, R. Sturgeon, G. Henry, A. Mayne, and R. Hurley, Scalability of Self-organizing Maps on a GPU cluster using OpenCL and CUDA, Journal of Physics: Conference Series, p.12018, 2012.
DOI : 10.1088/1742-6596/341/1/012018

[. Cuda-c, Programming Guide 4.2, CURAND Library, CUDPP library, Profiler User's Guide, 2012.

H. Dinh-nguyen, I. Yoshihara, K. Yamamori, and M. Yasunaga, Implementation of an Effective Hybrid GA for Large-Scale Traveling Salesman Problems, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.37, issue.1, pp.92-99, 2007.
DOI : 10.1109/TSMCB.2006.880136

H. Ibrahim, G. Osman, and . Laporte, Metaheuristics: A bibliography, Annals of Operations research, vol.63, issue.5, pp.511-623, 1996.

H. Christos and . Papadimitriou, The euclidean travelling salesman problem is np-complete, Theoretical Computer Science, vol.4, issue.3, pp.237-244, 1977.

M. Pedemonte and H. Cancela, A cellular ant colony optimisation for the generalised Steiner problem, International Journal of Innovative Computing and Applications, vol.2, issue.3, pp.188-201, 2010.
DOI : 10.1504/IJICA.2010.033650

J. Pearl, Probabilistic reasoning in intelligent systems: networks of plausible inference, 2014.

M. Pedemonte, S. Nesmachnow, and H. Cancela, A survey on parallel ant colony optimization, Applied Soft Computing, vol.11, issue.8, pp.5181-5197, 2011.
DOI : 10.1016/j.asoc.2011.05.042

R. Colin and . Reeves, Modern heuristic techniques for combinatorial problems

G. Reinelt, TSPLIB???A Traveling Salesman Problem Library, ORSA Journal on Computing, vol.3, issue.4, pp.376-384, 1991.
DOI : 10.1287/ijoc.3.4.376

M. Randall and A. Lewis, A Parallel Implementation of Ant Colony Optimization, Journal of Parallel and Distributed Computing, vol.62, issue.9, pp.1421-1432, 2002.
DOI : 10.1006/jpdc.2002.1854

X. Ren and J. Malik, Learning a classification model for segmentation, Proceedings Ninth IEEE International Conference on Computer Vision, pp.10-17, 2003.
DOI : 10.1109/ICCV.2003.1238308

C. Yuheng-ren and I. Reid, gslic: a real-time implementation of slic superpixel segmentation CUDA by example: an introduction to general-purpose GPU programming, 2010.

M. Sánchez-oro, A. Sevaux, R. Rossi, A. Martí, and . Duarte, Solving dynamic memory allocation problems in embedded systems with parallel variable neighborhood search strategies, Electronic Notes in Discrete Mathematics, vol.47, pp.85-92, 2015.
DOI : 10.1016/j.endm.2014.11.012

D. Scharstein and R. Szeliski, High-accuracy stereo depth maps using structured light, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., p.195, 2003.
DOI : 10.1109/CVPR.2003.1211354

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.6857

C. Shen and W. Tsai, A graph matching approach to optimal task assignment in distributed computing systems using a minimax criterion, Computers IEEE Transactions on, vol.100, issue.3, pp.197-203, 1985.

I. Stojmenovic, Honeycomb networks, IEEE Transactions on, vol.8, issue.10, pp.1036-1042, 1997.
DOI : 10.1007/3-540-60246-1_133

T. Stützle, Parallelization strategies for Ant Colony Optimization, Parallel Problem Solving from Nature PPSN V, pp.722-731, 1998.
DOI : 10.1007/BFb0056914

R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov et al., A comparative study of energy minimization methods for markov random fields with smoothness-based priors. Pattern Analysis and Machine Intelligence, Tal09] El-Ghazali Talbi. Metaheuristics: from design to implementation, pp.1068-1080, 2008.

F. Marshall, . Tappen, T. William, and . Freeman, Comparison of graph cuts with belief propagation for stereo, using identical mrf parameters, Computer Vision Ninth IEEE International Conference on, pp.900-906, 2003.

A. Tefas, C. Kotropoulos, and I. Pitas, Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.23, issue.7, pp.735-746, 2001.

M. Tomassini, Parallel and distributed evolutionary algorithms: A review, 1999.

Y. Taguchi, B. Wilburn, and L. Zitnick, Stereo reconstruction with mixed pixels using adaptive over-segmentation, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587691

[. Veksler, Efficient graph-based energy minimization methods in computer vision, 1999.

[. Van-luong, N. Melab, and E. Talbi, Gpu computing for parallel local search metaheuristic algorithms. Computers, IEEE Transactions on, vol.62, issue.1, pp.173-185, 2013.

J. Martin, . Wainwright, S. Tommi, A. S. Jaakkola, and . Willsky, Map estimation via agreement on trees: message-passing and linear programming. Information Theory, IEEE Transactions on, issue.11, pp.513697-3717, 2005.

[. Wang, N. Zhang, and J. Créput, A Massive Parallel Cellular GPU Implementation of Neural Network to Large Scale Euclidean TSP, Advances in Soft Computing and Its Applications, pp.118-129, 2013.
DOI : 10.1007/978-3-642-45111-9_10

N. Wang, J. Zhang, J. Créput, Y. Moreau, and . Ruichek, Parallel structured mesh generation with disparity maps by gpu implementation. Visualization and Computer Graphics, IEEE Transactions on, vol.21, issue.9, pp.1045-1057, 2015.

L. Xu, J. Jia, and Y. Matsushita, Motion detail preserving optical flow estimation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.34, issue.9, pp.1744-1757, 2012.

M. Yoshimi, T. Kuhara, K. Nishimoto, M. Miki, and T. Hiroyasu, Visualization of Pareto Solutions by Spherical Self-Organizing Map and It???s acceleration on a GPU, Journal of Software Engineering and Applications, vol.05, issue.03, p.2012
DOI : 10.4236/jsea.2012.53020

N. Zhang, Cellular GPU Models to Euclidean Optimization Problems: Applications from Stereo Matching to Structured Adaptive Meshing and Traveling Salesman Problem, 2013.
URL : https://hal.archives-ouvertes.fr/tel-00982405

[. Zitnick and S. B. Kang, Stereo for Image-Based Rendering using Image Over-Segmentation, International Journal of Computer Vision, vol.22, issue.7, pp.49-65, 2007.
DOI : 10.1007/s11263-006-0018-8

H. Zhang, J. Wang, J. Créput, Y. Moreau, and . Ruichek, Cellular GPU Model for Structured Mesh Generation and Its Application to the Stereo-Matching Disparity Map, 2013 IEEE International Symposium on Multimedia, pp.53-60, 2013.
DOI : 10.1109/ISM.2013.18