INFORMAZIONI SU QUESTO ARTICOLO

Cita

[1] Ababei C., Yan Feng, Brent Goplen, Hushrav Mogal, Tianpei Zhang, Kia Bazargan, and Sachin S. Sapatnekar, Placement and Routing in 3D Integrated Circuits, Design and Test of Computers, Vol. 22, Issue: 6, IEEE ISSN: 0740-7475, 2005, (2005), 520-531Search in Google Scholar

[2] Alway G.G. and Martin D.W., An algorithm for reducing the bandwidth of matrix of symetrical configuration, The Computer Journal, Oxford Journals, 8/3, (1965), 264-27210.1093/comjnl/8.3.264Search in Google Scholar

[3] Antoine G., A. Kahoum, L. Grigori, and M. Sosonkina, A partitioning algo- rithm for block-diagonal matrices with overlap, Parallel Computing 34/6-8 Elsevier, 2008, (2008), 332-34410.1016/j.parco.2008.01.004Search in Google Scholar

[4] Arany I, L. Szoda, and W.F. Smyth, Minimizing the bandwidth of sparse matrices, Annales Univ. Sci. Budapest., Sect. Comp., vol. 9, (1973)Search in Google Scholar

[5] Arany I, Another method for finding pseudo-peripheral nodes, Annales Universitatis Scientiarum Budapestinensis de RolandoEtvos nominatae, tom4, (1983), 39-49Search in Google Scholar

[6] Arany I, The method of Gibbs-Poole-Stockmeyer is non-heuristic, Annales Univ. Sci. Budapest., Sect. Comp., vol. 4, (1983)Search in Google Scholar

[7] Arbenz P., Cleary A., Dongarra J., and Hegland M., Parallel numerical linear algebra. chapter: A comparison of parallel solvers for diagonally dominant and general narrow banded linear systemss, Parallel numerical linear algebra, Nova Science Publishers, Inc., Commack, (2001), 35-56Search in Google Scholar

[8] Bansal .R and Srivastava K., Memetic algorithm for the antibandwidth maxi- mization problem, Journal of Heuristics - HEURISTICS , vol. 17, no. 1, Springer, 2011, (2011), 39-6010.1007/s10732-010-9124-4Search in Google Scholar

[9] Barnand S.T., Pothen A., and Simon H.D., A spectral algorithm for envelope reduction of sparse matrices, Journal Num. Lin. Alg. With Appl. 2, (1995), 311-33410.1002/nla.1680020402Search in Google Scholar

[10] Baumann N., P. Fleishmann, and O. Mutzbauer, Double ordering and fill-in for the LU Factorization, SIAM J. Matrix Analysis and Applications, 25, (2003), 630-64110.1137/S0895479802392989Search in Google Scholar

[11] Berry M., B. Hendrickson, and P. Raghavan, Sparse matrix reordering schemes for browsing hypertext, S. Smale, J. Renegar, M. Shub (Eds.), Lectures in Applied Mathematics, 32: The Mathematics of Numerical Analysis, AMS, Providence, RI, 1996, (1996), 99-123Search in Google Scholar

[12] Benitez A. and Branas F., The Go-Away algorithm for Block Factorization of a Sparse Matrix, Course on algorithms for Sparse Large Scale Linear Algebraic Systems, NATO ASI SERIES, Vol. 508, Kluwer, Londres, 1998, (1998), 107-117Search in Google Scholar

[13] Bhatt S.N. and Leighton F.T., A framework for solving VLSI graph layout problems, Computer and System Sciences, Vol. 28, 1984, (1984), 300-34310.1016/0022-0000(84)90071-0Search in Google Scholar

[14] Blum C., M. J. Blesa Aguilera, A. Roli, and M. Sampels, Hybrid Meta- heuristics, An Emerging Approach to Optimization, volume 114 of Studies in Computational Intelligence. Springer, 2008, (2012)10.1007/978-3-540-78295-7Search in Google Scholar

[15] Bolanos M.E., S. Aviyente, and H. Radha, Graph entropy rate minimization and the compressibility of undirected binary graphs, IEEE Statistical Signal Processing Workshop (SSP), 2012, (2012)10.1109/SSP.2012.6319634Search in Google Scholar

[16] Botafogo R.A., Cluster analysis for hypertext systems, Proceedings of the 16th Annul International ACM-SIGIR Conference on Research and Development in Information Retrieval, ISBN:0-89791-605-0, 1993, (1993), 116-12510.1145/160688.160704Search in Google Scholar

[17] Boman E.G. and Hendrickson B., A multilevel algorithm for reducing the enve- lope of sparse matrices, Tech. Rep. SCCM-96-14, Stanford University, 1996, (1996)Search in Google Scholar

[18] Boutora Y., R. Ibtiouen, S. Mezani, N. Takorabet, and A. Rezzoug, A new fast method of profile and wavefront reduction for cylindrical structures in finite elements method analysis, Progress In Electromagnetics Research B, Vol. 27, 2011, (2011), 349-36310.2528/PIERB10110703Search in Google Scholar

[19] Campos V., Pinana E., and Marti R., Adaptive Memory Programming for Matrix Bandwidth Minimization, Annals of Operations Research, March 2011, Vol. 183, Issue 1, Springer 2011, (2011), 7-2310.1007/s10479-009-0573-9Search in Google Scholar

[20] Caprara A. and Salazar-Gonzales J.J., Laying Out Sparse Graphs with Prov- ably Minimum Bandwidth, INFORMS Journal on Computing Vol. 17, No. 3, Summer 2005, ISSN:1091-9856, (2005), 356-37310.1287/ijoc.1040.0083Search in Google Scholar

[21] Caproni A., F. Cervelli, M. Mongiardo, L. Tarricone, and F. Malucelli, Bandwidth Reduced Full-Wave Simulation of Lossless and Thin Planar Microstrip Circuits, ACES JOURNAL, vol. 13, no. 2, (1998), 197-204Search in Google Scholar

[22] Chan W.M. and George A., A linear time implementation of the Reverse Cuthill- McKee algorithm, BIT Numerical Mathematics, vol. 20, no. 1, (1980), 8-1410.1007/BF01933580Search in Google Scholar

[23] Chan G.K. and M. Head-Gordon, Highly correlated calculations with a polyno- mial cost algorithm: A study of the density matrix renormalization group, The Journal of Chemical Physics, vol. 116, issue 11, (2002); American Institute of Physics Publishing, doi: 10.1063/1.1449459, 2002, (2002)Search in Google Scholar

[24] Clift S.S., Simon H.D., and Tang Wei-Pai, Spectral Ordering Techniques for Incomplete LU Preconditioners for CG Methods, RIACS Technical Report 95.20 September 1995, Queens Univ., (1995)Search in Google Scholar

[25] Corso G.D. and Manzini G., Finding exact solutions to the bandwidth mini- mization problem, Computing 62, 3, (1999), 189-20310.1007/s006070050002Search in Google Scholar

[26] Corso G.D. and Romani F., Heuristic spectral techniques for the reduction of bandwidth and work-bound of sparse matrices, Numerical Algorithms 28, (2001), 127-136Search in Google Scholar

[27] Crisan G.C. and Pintea C.M., A hybrid technique for matrix bandwidth prob- lem, University of Bacu Faculty of Sciences, Scientific Studies and Research, Series Mathematics and Informatics, Vol. 21 (2011), No. 1, (2011), 113-120Search in Google Scholar

[28] Cuthill E. and J. McKee, Reducing the bandwidth of sparse symmetric matrices, Proc. of ACM, (1969), 157-172.10.1145/800195.805928Search in Google Scholar

[29] Czibula G., Crisan G.C., Pintea C.M., and Czibula I.G., Soft Computing approaches on the Bandwidth Problem, INFORMATICA 24/2 2013, (2013), 169-18010.15388/Informatica.2013.390Search in Google Scholar

[30] E. F. D'Azevedo, P. A. Forsyth, and Wei-Pai Tang, Ordering methods for preconditioned conjugate gradient methods applied to unstructured grid problems, SIAM Journal on Matrix Analysis and Applications, Volume 13 Issue 3, July 1992, (1992), 944-96110.1137/0613057Search in Google Scholar

[31] Diaz J., The fi operator, Fundamentals of Computation Theory, Ed. Akademie- Verlag, (1979), 105-111Search in Google Scholar

[32] Duarte A., R. Marti, M.G.C. Resende, and R.M.A. Silva, GRASP with path relinking heuristics for the antibandwidth problem, Networks, (2011). doi: 10.1002/net.20418., (2011)10.1002/net.20418Search in Google Scholar

[33] Dueck G.H. and Jefis J., A heuristic bandwidth minimization algorithm, Journal of Combinatorial Mathematics and Combinatorial Computing 18, (1995), 97-108Search in Google Scholar

[34] DufiIain S. and Gerard A. Meurant, The efiect of ordering on preconditioned conjugate gradients, BIT Numerical Mathematics 1989, Volume 29, Issue 4, (1989), 635-65710.1007/BF01932738Search in Google Scholar

[35] Dutot A., D. Olivier, and G. Savin, The fioperator, Proceedings of EPNACS 2011 within ECCS'11 Emergent Properties in Natural and Artificial Complex Systems, Vienna, Austria - September 15, 2011, (2011)Search in Google Scholar

[36] Ellen M.B. Cavalheiro, Daniele C. Silva, and Sheila M. de Almeida, Aplica- cao de Algoritmos Geneticos no Reordenamento deMatrizes Esparsas, Anais do Congresso de Matematica Aplicada e Computacional CMAC de Nordeste, ISSN:2317-3297, 2013, (2013)Search in Google Scholar

[37] Esposito A. and Tarricone L., Parallel heuristics for bandwidth reduction of sparse matrices with IBM SP2 and Cray T3D, Springer, Applied Parallel Computing Industrial Computation and Optimization LNCS Vol. 1184, (1996), 239-24610.1007/3-540-62095-8_25Search in Google Scholar

[38] Esposito A., M.S. Catalano, F. Malucelli, and L. Tarricone, Sparse matrix bandwidth reduction: Algorithms, applications and real industrial cases in electro- magnetics, high performance algorithms for structured matrix problems, Advances in the theory of Computation and Computational Mathematics 2, (1998), 27-45Search in Google Scholar

[39] Esposito A., F. Malucelli, and Tarricone L., Bandwidth and Profile reduction of Sparse Matrices: An Experimental Comparison of New Heuristics, Proc. of Algorithms and Experiment (ALEX98) febr. 1998, R.Battiti and A.A. Bertossi (Eds), (1998), 19-26Search in Google Scholar

[40] Everstine G.C., The BANDIT program for the reduction of matrix bandwidth for NASTRAN, Naval Ship Research development center, computation and mathematics, Department research and development report, Report 3827/1972, (1972)Search in Google Scholar

[41] Everstine G.C., Finite Element formulation of structural acoustics problems, Computers and Srrucmres Vol. 65, No. 3, Elsevier, 1997, (1997), 307-32110.1016/S0045-7949(96)00252-0Search in Google Scholar

[42] Fernando L. Alvaro and Zian Wang, Direct Sparse Interval Hull Computations for Thin Non-M-Matrices, Interval Computations No 2, 1993, (1993)Search in Google Scholar

[43] Garey M., Graham R., and Knuth D., Complexity results for bandwidth min- imization, SIAM J. Appl. Math. 34, (1978), 477-49510.1137/0134037Search in Google Scholar

[44] George J.A., Computer implementation of the finite element method, Standford Computer Science Dept., Tech. Report STAn-CS-71-208, Standford, California, (1971)Search in Google Scholar

[45] George A. and Pothen A., An Analysis of Spectral Envelope Reduction via Quadratic Assignment Problems, SIAM. J. Matrix Anal. and Appl., 18/3, (2006), 706-73210.1137/S089547989427470XSearch in Google Scholar

[46] Ghidetti K., L. Catabriga, M.C. Boeres, and M.C. Rangel, A study of the inuence of sparse matrices reordering algorithms on Krylov-type preconditioned iterative methods, Mecanica Computacional Vol XXIX, 2010, (2010), 2323-2343Search in Google Scholar

[47] Gibbs N.E., Poole W.G., and Stockmeyer P.K., An algorithm for reducing the bandwidth and proe of a sparse matrix, SIAM Journal on Numerical Analysis, 13, (1976), 236-25010.1137/0713023Search in Google Scholar

[48] Glover F. and Laguna M., "Tabu Search" in Modern Heuristic Techniques for Combinatorial Problems, Ed. C. Reeves, Blackwell Sc. Publ., Oxford, (1993), 70-150Search in Google Scholar

[49] Glover F., Scatter search and path relinking, New Ideas in Optimization, McGraw- Hill Ltd., 1999., (1999), 297-316Search in Google Scholar

[50] Golub G.H. and Plemonts R.J., Large-Scale Geodetic Least-Squares Adjustment by Dissection and Orthogonal Decomposition, Linear Algebra and its Application, 34, Elsevier, (1980), 3-2710.1016/0024-3795(80)90156-1Search in Google Scholar

[51] Grama A., Naumov M., and Sameh A., Evaluating sparse linear system solvers on scalable parallel architectures, AFRL-RI-RS-TR-2008-273 Final Technical Report October 2008, Purdue University, (2008)10.21236/ADA487623Search in Google Scholar

[52] Greiner D. and Winter G., Sparse Matrices Reordering using Evolutionary Algo- rithms:A Seeded Approach, Proc. ERCOFTAC 2006 Design Optimization: Methods and Applications, Las Palmas de Gran Canaria, 2006, (2006)Search in Google Scholar

[53] Guevara R.L., Reducing the Bandwidth of a Sparse Symmetric Matrix with Ge- netic Algorithmic, GEM, CSREA Press, (2010), (2010), 209-214Search in Google Scholar

[54] Gupta P.K., For eficient parallel solution of load ow problem, Project report, Dept. Of. El. Eng., Indian Institute of Science, Bangalore, (1995)Search in Google Scholar

[55] Gurari E. and Sudborough I., Improved dynamic programming algorithms for bandwidth minimization and the min-cut linear arrangement problem, Journal of Algorithms, Vol. 5, No. 4, Elsevier, (1984), 531-54610.1016/0196-6774(84)90006-3Search in Google Scholar

[56] Hager W.W., Minimizing the profile of a symmetric matrix, Siam J. Sci. Comput. vol. 23, no. 5, (2002), 1799-181610.1137/S1064827500379215Search in Google Scholar

[57] Harary F., Graph Theory, Addison-Wesley, (1969) [58] Harper L.H., Optimal assignments of numbers to vertices, J. Soc. Indust. Appl. Math., Vol. 12, No. 1, (1964), 131-135Search in Google Scholar

[59] Harper L.H., Optimal numberings and isoperimetric problems on graphs, J. Combin. Theory, Vol. 1, (1966), 385-39310.1016/S0021-9800(66)80059-5Search in Google Scholar

[60] Huang H., J.M. Dennis, L. Wang, and P. Chen, A scalable parallel LSQR algorithm for solving large-scale linear system for tomographic problems: a case study in seismic tomography, ICCS 2013, Procedia Computer Science 18, Elsevier, 2013, (2013), 581-590Search in Google Scholar

[61] Isazadeh A., Izadkhah H., and Mokarram A.H., A Learning based Evolution- ary Approach for Minimization of Matrix Bandwidth Problem, Appl. Math. Inf. Sci. 6, No. 1, (2012), 51-57Search in Google Scholar

[62] Jennings A., A compact storage scheme for the solution of symmetric linear simul- taneous equations, Computer Journal 9, (1966), 281-28510.1093/comjnl/9.3.281Search in Google Scholar

[63] Karp R., Mapping the Genome: Some Combinatorial Problems Arising in Molecular Biology, STOC'93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing, 1993, (1993)Search in Google Scholar

[64] Kaveh A. and Sharafi P., A simple ANT algorithm for profile optimization of sparse matrix, Asian Journal of Civil Engineering vol. 9, no. 1, (2007), 35-46Search in Google Scholar

[65] Kaveh A. and Sharafi P., Ordering for bandwidth and profile minimization prob- lems via charged system search algorithm, IJST, Transactions of Civil Engineering, Vol. 36, No. C1, (2012), 39-52Search in Google Scholar

[66] Kennedy J. and Eberhart R., Particle Swarm Optimization, IEEE International Conference on Neural Networks (Perth, Australia), IEEE Service Center, Piscataway, NJ, IV, (1995), 1942-1948Search in Google Scholar

[67] Kendall R., Incidence Matrices, Interval Graphs and Seriation in archaeologys, Pacific Journal of Mathematics, vol. 28, no. 3 1969, (1969)10.2140/pjm.1969.28.565Search in Google Scholar

[68] King P., An automatic reordering scheme for simultaneous equations derived from network systems, Int. J. Numer. meth. Eng. 2, (1970), 523-53310.1002/nme.1620020406Search in Google Scholar

[69] Konig G., M. Moldaschl, and W.N. Gansterer, Computing eigenvectors of block tridiagonal matrices based on twisted block factorizations, Journal of Computational and Applied Mathematics 236, Elsevier, 2012, (2012)10.1016/j.cam.2011.07.010Search in Google Scholar

[70] Koohestani B. and Corne D.W., An Improved Fitness Function and Mutation Operator for Metaheuristic Approaches to the Bandwidth Minimization Problem, AIP Conference Proceedings 1117, 21, doi: 10.1063/1.3130627, 2009, (2009)10.1063/1.3130627Search in Google Scholar

[71] Koohestani B. and Poli R., A Genetic Programming Approach to the Matrix Bandwidth-Minimization Problem, R. Schaefer et al. (Eds.): PPSN XI, Part II, LNCS 6239, Springer-Verlag Berlin Heidelberg 2010, (2010), 482-491Search in Google Scholar

[72] Koohestani B. and Poli R., A Hyper-Heuristic Approach to Evolving Algorithms for Bandwidth Reduction Based on Genetic Programming, SGAI Conf., Springer 2011, (2011), 93-10010.1007/978-1-4471-2318-7_7Search in Google Scholar

[73] Koohestani B. and Poli R., A Genetic Programming Approach for Evolving Highly-Competitive General Algorithms for Envelope Reduction in Sparse Matrices, C.A. Coello Coello et al. (Eds.): PPSN 2012, Part II, LNCS 7492, Springer, 2012., (2012), 287-296Search in Google Scholar

[74] Kratsch D., Finding the minimum bandwidth of an interval graph, Inform. Comput. 74, (1987), 140-18710.1016/0890-5401(87)90028-9Search in Google Scholar

[75] Kumfert G. and Pothen A., Two improved algorithms for envelope and wavefront reduction, BIT Numerical Mathematics, 37/3, (1997), 559-59010.1007/BF02510240Search in Google Scholar

[76] Leung J.Y.-T, Vornberger O., and Witthofi J.D, On some variants of the bandwidth minimization problem, SIAM J. on Computing, 13, (1984), 650-66710.1137/0213040Search in Google Scholar

[77] Levin M.P., Compound algorithm for decreasing of matrix profile size, Trends in Mathematics, Inform. Center for Math. Sc., vol 9, no. 1, June 2006, (2006), 141-148Search in Google Scholar

[78] Lim A., Lin J., and Xiao F., Particle Swarm Optimization and Hill Climbing to Solve the Bandwidth Minimization Problem, MIC2003: The Fifth Metaheuristics International Conference, Kyoto, Japan, August 2528, 2003, (2003)Search in Google Scholar

[79] Lim A., Rodrigues B., and Xiao F., Integrated Genetic Algorithm with Hill Climbing for Bandwidth Minimization Problem, E. Cantu-Paz et al. (Eds.): GECCO 2003, LNCS 2724, Springer-Verlag Berlin Heidelberg, 2003, (2003), 1594-1595Search in Google Scholar

[80] Lim A., Rodrigues B., and Xiao F., A Centroid-based approach to solve the Bandwidth Minimization Problem, Proceedings of the 37th Hawaii International Conference on System Sciences, CPS 0-7695-2056-1/04 IEEE, 2004, (2004)10.1109/HICSS.2004.1265221Search in Google Scholar

[81] Lim A., Lin J., Rodrigues B., and Xiao F., Ant colony optimization with hill climbing for the bandwidth minimization problem, Elsevier, Applied Soft Computing 6/2, (2006), 180-18810.1016/j.asoc.2005.01.001Search in Google Scholar

[82] Lim A., Rodrigues B., and Xiao F., Heuristics for matrix bandwidth reduction, Elsevier, European Journal of Operational Research 174, (2006), 69-9110.1016/j.ejor.2005.02.066Search in Google Scholar

[83] Lozano M., Duarte A., Gortazar F., and Marti R, Variable neighborhood search with ejection chains for the antibandwidth problem, Journal of Heuristics, 18/6, Springer, (2012), 919-93810.1007/s10732-012-9213-7Search in Google Scholar

[84] Lozano M., Duarte A., Gortazar F., and Marti R, A hybrid metaheuristic for the cyclic antibandwidth problem, Knowledge-Based Systems 54, Elsevier, (2013), 103-11310.1016/j.knosys.2013.08.026Search in Google Scholar

[85] Luo J.C., Algorithms for reducing the bandwidth and profile of a sparse matrix, Computers and Structures 44 (1992), (1992), 535-54810.1016/0045-7949(92)90386-ESearch in Google Scholar

[86] Mafteiu-Scai L.O., Bandwidth reduction on sparse matrix, West University of Timisoara Annals, XLVIII/3, (2010)Search in Google Scholar

[87] Mafteiu-Scai L.O., Negru V., Zaharie D., and Aritoni O., Average bandwidth reduction in sparse matrices using hybrid heuristics, Studia Universitatis Babes- Bolyai University, Cluj Napoca, 3/2011, (2011)Search in Google Scholar

[88] Mafteiu-Scai L.O., Negru V., Zaharie D., and Aritoni O., Average bandwidth reduction in sparse matrices using hybrid heuristics-extended version, Proc. KEPT 2011, selected papers, ed. M. Frentiu et. all, Cluj-Napoca, July 4-6, 2011, Presa Universitara Clujeana, ISSN 2067-1180, (2011), 379-389Search in Google Scholar

[89] Mafteiu-Scai L.O., Interchange opportunity in average bandwidth reduction in sparse matrix, West Univ. of Timisoara Annals, Timisoara, Romania, ISSN:1841-3293, (2012)10.2478/v10324-012-0015-2Search in Google Scholar

[90] Mafteiu-Scai L.O., Average Bandwidth Relevance n Parallel Solving Systems of Linear Equations, IJERA Vol. 3, Issue 1, January-February 2013, ISSN 2248-9622, (2013), 1898-1907Search in Google Scholar

[91] Mafteiu-Scai L.O., Experiments and Recommendations for Partitioning Systems of Equations, West Univ. of Timisoara Annals, Timisoara, Romania, LI 1/2014, ISSN:1841-3293, (2014), 141-15610.2478/awutm-2014-0009Search in Google Scholar

[92] Maheswaran M., K.J. Webb, and H.J. Siegel, A Modified Conjugate Gradient Squared Algorithm for Nonsymmetric Linear Systems, The Journal of Supercomputing, 14, Kluwer Academic Publishers , 1999, (1999), 257-28010.1023/A:1008141600003Search in Google Scholar

[93] Marti R., M. Laguna, F. Glover, and V. Campos, Reducing the bandwidth of a sparse matrix with tabu search, European Journal of Operational Research 135 (2), (2001), 211-22010.1016/S0377-2217(00)00325-8Search in Google Scholar

[94] Marti R., Campos V., and Pinana E., A Branch and Bound Algorithm for the Matrix Bandwidth Minimization, European Journal of Operational Research, 186/2, (2008), 513-52810.1016/j.ejor.2007.02.004Search in Google Scholar

[95] Maruster S., Negru V., and Mafteiu-Scai L.O., Experimental study on parallel methods for solving systems of equations, SYNACS Timisoara, 2012, IEEE Xplore CPS ISBN: 978-1-4673-5026-6, DOI: 10.1109/SYNASC.2012.7, (2013)10.1109/SYNASC.2012.7Search in Google Scholar

[96] Mecke S. and Wagner D., Solving Geometric Covering Problems by Data Re- duction, Algorithms ESA 2004, Lecture Notes in Computer Science Volume 3221, 2004, (2004), 760-77110.1007/978-3-540-30140-0_67Search in Google Scholar

[97] N. Mladenovic, D. Urosevic, D. Perez-Brito, and C.G. Garcia-Gonzalez, Variable neighbourhood search for bandwidth reduction, European Journal of Operational Research 200, Elsevier, (2010), 14-2710.1016/j.ejor.2008.12.015Search in Google Scholar

[98] Mueller C., Sparse Matrix Reordering Algorithms for Cluster Identification, For I532, Machine Learning in Bioinformatics, December 17, 2004, (2004)Search in Google Scholar

[99] Osipov P., Simple heuristic algorithm for profile reduction of arbitrary sparse ma- trix, Applied Mathematics and Computation, Vol 168/2, Elsevier, (2005), 848-85710.1016/j.amc.2004.09.052Search in Google Scholar

[100] Pan V., Optimum parallel computation with band matrices, TR-93-061, NSF Grant CRR9020690 1993, (1993)Search in Google Scholar

[101] Papadimitriou C.H., The NP-completeness of the bandwidth minimization prob- lem, Computing 16, 3, (1976), 263-27010.1007/BF02280884Search in Google Scholar

[102] Pinana E., Plana I., Campos V., and Marti R., GRASP and path relinking for the matrix bandwidth minimization, European Journal of Operational Research 153 (1,16), (2004), 200-21010.1016/S0377-2217(02)00715-4Search in Google Scholar

[103] Pinar A. and Heath M.T., Improving performance of sparse matrix-vector mul- tiplication, Proceeding SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing Article No. 30, ISBN:1-58113-091-0, (1999)10.1145/331532.331562Search in Google Scholar

[104] Pintea C.M., Crisan G.C., and Chira C., A Hybrid ACO Approach to the Matrix Bandwidth Minimization Problem, M. Graa Romay et al. (Eds.): HAIS 2010, Part I, LNAI 6076, Springer-Verlag Berlin Heidelberg 2010, (2010), 407-414Search in Google Scholar

[105] Pintea C.M. and Vescan A., Bio-Inspired Components for Bandwidth Problem, "Vasile Alecsandri" University of Bacu, Faculty of Sciences, Scientific Studies and Research, Series Mathematics and Informatics, Vol. 21 (2011), No. 1, (2011), 185-192Search in Google Scholar

[106] Pintea C.M., Advances in Bio-inspired Computing for Combinatorial Optimization Problems, Intelligent Systems Reference Library, Vol. 57, Springer, ISBN 978-3-642-40178-7, (2014)10.1007/978-3-642-40179-4_1Search in Google Scholar

[107] Poli R., Covariant tarpeian method for bloat control in genetic programming, Riolo, R., McConaghy, T., Vladislavleva, E. (eds.) Genetic Programming Theory and Practice VIII, Genetic and Evolutionary Computation, vol. 8, chap. 5, Springer, (2014), 71-9010.1007/978-1-4419-7747-2_5Search in Google Scholar

[108] Pop P. and Matei O., An Improved Heuristic for the Bandwidth Minimization Based on genetic programming, Proceedings part II Hybrid Artificial Intelligent Systems: 6th International Conference, HAIS Poland 2011, (2011), 67-7510.1007/978-3-642-21222-2_9Search in Google Scholar

[109] Pop P. and Matei O., Reducing the bandwidth of a sparse matrix with a genetic algorithm, Optimization: A Journal of Mathematical Programming and Operations Research, Vol. 63, Issue 12, 2014, (2014), 1851-1876Search in Google Scholar

[110] Pop P. and Matei O., An Eficient Metaheuristic Approach for Solving a Class of Matrix Optimization Problems, Proceedings of the 15th EU/ME 2014 Workshop, ISBN 978-605-85313-0-7, (2014), 17-25Search in Google Scholar

[111] Quoct V. and O'Learys J.R., AUTOMATIC NODE RESEQUENCING WITH CONSTRAINTS, Computers and Structures Vol. 18, No. 1, (1984), 55-6910.1016/0045-7949(84)90082-8Search in Google Scholar

[112] Rainer G., Bandwidth reduction on sparse matrices by introducing new variables, Ingeniare. Revista chilena de ingeniera, vol. 18 No. 3, (2010), 395-40010.4067/S0718-33052010000300013Search in Google Scholar

[113] Ramon P. and Benitez A., On Reducing Bandwidth of Matrices in the Go-Away Algorithm for Regular Grids, Divulgaciones Matematicas Vol. 7 No. 1, 1999, (1999), 1-12Search in Google Scholar

[114] Raspaud A., Schroder H, Sykora O., Torok L., and Vrto I., Antibandwidth and cyclic antibandwidth of meshes and hypercubes, Discrete Mathematics, 309, (2009), 3541-355210.1016/j.disc.2007.12.058Search in Google Scholar

[115] Ravi R., Agrawal A., and Klein P., Ordering problems approximated: single- processor scheduling and interval graph Completition, Proc. Automata, Languages and Programming, Springer, ISBN: 0-387-54233-7, (1991), 751-762Search in Google Scholar

[116] Reid J.K. and Scott J.A., Reducing the total bandwidth of a sparse unsymmetric matrix, RAL-TR-2005-001 CCLRC ISSN 1358-6254, (2005)Search in Google Scholar

[117] Rosen R., Matrix bandwidth minimization, In Proc. 23rd Nat. Conf. ACM, (1968), 585-59510.1145/800186.810622Search in Google Scholar

[118] Saxe J.B., GRASP with Path Relinking for the SumCut Problem, International Journal of Combinatorial Optimization Problems and Informatics, Vol. 3, No. 1, Jan-Aprilie 2012, ISSN: 2007-1558, (2012), 3-11Search in Google Scholar

[119] Saxe J.B., Dynamic programming algorithms for recognizing small bandwidth graphs in polynomial time, SIAM Journal of Algebraic and Discrete Methods 1, (1980), 363-36910.1137/0601042Search in Google Scholar

[120] Sloan S.M., An algorithm for profile and wavefront reduction of sparse matri- ces, International Journal for Numerical Methods in Engineering. Vol. 23, Issue 2, February, 1985, (1985), 239-25110.1002/nme.1620230208Search in Google Scholar

[121] Smyth W.F. and Arany I., Another algorithm for reducing bandwidth and profile of a sparse matrix, AFIPS '76 Proceedings, ACM 1976, (1976)10.1145/1499799.1499935Search in Google Scholar

[122] Smyth W.F., Algorithms for the reduction of matrix bandwidth and profile, Journal of Computational and Applied Mathematics 12-13, (1985), 551-56110.1016/0377-0427(85)90048-2Search in Google Scholar

[123] Snay R.A., Reducing the profile of sparse symmetric matrices, NOAA Technical Memorandum NOS NGS-4, 1976, (1976)10.1007/BF02521587Search in Google Scholar

[124] Taniguchi T., Bandwidth Minimization Algorithm for Finite Element Mesh, Memoirs of the School of Engineering, Okayama University, Vol. 16, No.1, (1981)Search in Google Scholar

[125] Taniguchi T., Reordering Algorithm for Skyline Method (Numerical Algorithms of Large Linear Problems), KURENAI : Kyoto University Research Information Repository, 1985-02, (1985), 30-49Search in Google Scholar

[126] Rodriguez-Tello E. and Betancourt L.C., An Improved Memetic Algorithm for the Antibandwidth Problem, Artificial Evolution, LNCS Springer, Vol. 7401, 2012, (2012), 121-13210.1007/978-3-642-35533-2_11Search in Google Scholar

[127] Tewarson R.P., Sparse Matrices, Elsevier, Academic press, 99, (1973)Search in Google Scholar

[128] Torok L. and Vrto I., Antibandwidth of 3-dimensional meshes, Electronic Notes in Discrete Mathematics, 28, (2007), 161-16710.1016/j.endm.2007.01.023Search in Google Scholar

[129] Torres-Jimenez J. and Rodriguez-Tello E., A New Measure for the Bandwidth Minimization Problem, Advances in Artificial Intelligence, LNCS, vol. 1952, 2000, Springer, ISBN 978-3-540-41276-2, (2000), 477-48610.1007/3-540-44399-1_49Search in Google Scholar

[130] Rodriguez-Tello E., Hao K-K., and Torres-Jimenez J., An Improved Simu- lated Annealing Algorithm for Bandwidth Minimization, European Journal of Operational Research 185, (2008), 1319-133510.1016/j.ejor.2005.12.052Search in Google Scholar

[131] Tsao Y.P. and Chang G.D., Profile minimization on compositions of graphs, NCTS/TPE-Math Technical Report 2006-007, (2005)Search in Google Scholar

[132] Ullman J.D., Computational aspects of VLSI, Computer Science Press, Rockville, Md., 1983, (1983)Search in Google Scholar

[133] Wai-Hung L. and Sherman A.H., Comparative analysis of the CutHill-McKee and the Reverse CutHill-Mckee ordering algorithms for sparse matrices, SIAM J. Numer. Anal., 13, (1976), 198-21310.1137/0713020Search in Google Scholar

[134] Wang Q., Y. C. Guo, and X. W. Shi, An improved algorithm for matrix band- width and profile reduction in finite element analysis, Progress In Electromagnetics Research Letters, 9, (2009), 29-3810.2528/PIERL09042305Search in Google Scholar

[135] Weise T., Global Optimization Algorithms " Theory and Application ", e-book, 3rd edition, http://www.it-weise.de/projects/bookNew.pdf, (2011) Search in Google Scholar

[136] Xu S., H.X. Lin, and W. Xue, Sparse Matrix-Vector Multiplication Optimiza- tions based on Matrix Bandwidth Reduction using NVIDIA CUDA, Int. Sym. on Distrib. Comp. and App. to Business, Eng. and Science, IEEE CPS, ISBN:978-1-4244-7539-1, 2010, (2010), 609-61410.1109/DCABES.2010.162Search in Google Scholar

[137] Yixun L. and Jinjiang Y., The dual bandwdith problem for graphs, Journal of Zhengzhou University, 35 (2003), (2003), 1-5Search in Google Scholar

[138] Zabih R., Some Applications of Graph Bandwidth to Constraint Satisfaction Prob- lems, AAAI-90 Proceedings, AAAI (www.aaai.org), 1990, (1990) Search in Google Scholar

eISSN:
1841-3307
Lingua:
Inglese
Frequenza di pubblicazione:
Volume Open
Argomenti della rivista:
Mathematics, General Mathematics