Basilis Mamalis, Grammati Pantziou, Georgios Dimitropoulos, and Dimitris Kremmydas
[1] K. Murty, Linear programming (New York, NY: John Wiley& Sons, 1983). [2] J.A. Hall, Towards a practical parallelization of the simplex method, Computational Management Science, 7(2), 2010, 139–170. [3] G. Yarmish and R.V. Slyke, A distributed scaleable simplex method, Journal of Supercomputing, 49(3), 2009, 373–381. [4] E.S. Badr, M. Moussa, K. Paparrizos, N. Samaras, andA. Sifaleras, Some computational results on MPI parallel implementation of dense simplex method, World Academy ofScience, Engineering and Technology (WASET ), 23, 2008,778–781. [5] J. Qin and D.T. Nguyen, A parallel-vector simplex algorithm on distributed-memory computers, Structural Optimizations, 11(3), 1996, 260–262. [6] M. Lubin, J.A. Hall, C.G. Petra, and M. Anitescu, Parallel distributed-memory simplex for large-scale stochastic LP problems, Computational Optimization and Applications, 55(3), 2013, 571–596. [7] K.K. Sivaramakrishnan, A parallel interior point decomposition algorithm for block angular semidefinite programs, Computational Optimization and Applications, 46(1), 2010, 1–29. [8] M. Geva and Y. Wiseman, Distributed shared memory integration, Proc. IEEE Conf. on Information Reuse and Integration, Las Vegas, NV, 2007, 146–151. [9] J.A. Hall and K. McKinnon, ASYNPLEX an asynchronousparallel revised simplex algorithm, Annals of Operations Research, 81, 1998, 27–49. [10] W. Shu and M.Y. Wu, Sparse implementation of revisedsimplex algorithms on parallel computers, Proc. 6th SIAMConf. in Parallel Processing for Scientific Computing, Norfolk, VA, 1993, 501–509. [11] M.E. Thomadakis and J.C. Liu, An efficient steepest-edge simplex algorithm for SIMD computers, Proc. Int. Conf. on Supercomputing, Philadelphia, PA, 1996, 286–293. [12] J. Eckstein, I. Boduroglu, L. Polymenakos, and D. Goldfarb, Data-parallel implementations of dense simplex methods on the connection machine CM-2, ORSA Journal on Computing, 7(4), 1995, 402–416. [13] C.B. Stunkel, Linear optimization via message-based parallel processing, Proc. Int. Conf. on Parallel Processing, Pennsylvania, PA, 1988, 264–271. [14] D. Klabjan, L.E. Johnson, and L.G. Nemhauser, A parallel primal–dual simplex algorithm, Operations Research Letters, 27(2), 2000, 47–55. [15] I. Maros and G. Mitra, Investigating the sparse simplex method on a distributed memory multiprocessor, Parallel Computing, 26(1), 2000, 151–170. [16] S.S. Chen, D.L. Donoho, and M.A. Saunders, Atomic decomposition by basis pursuit, SIAM Journal on Scientific Computing, 20(1), 1998, 33–61. [17] I.W. Selesnick, R.V. Slyke, and O.G. Guleryuz, Pixel recovery via l1 minimization in the wavelet domain, Proc. Int. Conf. on Image Processing, Singapore, 2004, 1819–1822. [18] E. Gislason, M. Johansen, K. Conradsen, and B. Ersboll, Three different criteria for the design of two-dimensional zero phase FIR digital filters, IEEE Transactions on Signal Processing, 41(10), 1993, 3070–3074. [19] K. Steiglitz, T.W. Parks, and J.F. Kaiser, METEOR: aconstraint-based FIR filter design program, IEEE Transactions on Signal Processing, 40(8), 1992, 1901–1909. [20] S.P. Bradley, U.M. Fayyad, and O.L. Mangasarian, Mathematical programming for data mining: formulations and challenges,INFORMS Journal on Computing, 11(3), 1999, 217–238. [21] B. Mamalis, G. Pantziou, D. Kremmydas, and G. Dimitropou-los, Reexamining the parallelization schemes for standard full tableau simplex method on distributed memory environments, Proc. 10th IASTED PDCN Conf., Innsbruck, Austria, 2011, 115–123.
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