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An improved targeted climbing algorithm for linear programs
1.  School of Mathematical & Geospatial Sciences, RMIT University, Melbourne, Australia, Australia 
References:
[1] 
H. Arsham, A hybrid gradient and feasible direction pivotal solution algorithm for general linear programs, Applied Mathematics and Computation, 188 (2007), 596611. Google Scholar 
[2] 
H. Arsham, T. Damij and J. Grad, An algorithm for simplex tableau reduction: the pushtopull solution strategy, Applied Mathematics and Computation, 137 (2003), 525547. Google Scholar 
[3] 
E. Barnes, V. Chen, B. Gopalakrishnan and E. L. Johnson, A leastsquares primaldual algorithm for solving linear programming problems, Operations Research Letters, 30 (2002), 289294. doi: 10.1016/S01676377(02)001633. Google Scholar 
[4] 
G. B. Dantzig, "Linear Programming and Extensions," Princeton University Press, Princeton, N. J., 1963. Google Scholar 
[5] 
N. Karmarkar, A new polynomialtime algorithm for linear programming, Combinatorica, 4 (1984), 373395. doi: 10.1007/BF02579150. Google Scholar 
[6] 
Y. Liu, An exterior point linear programming method based on inclusive normal cones, Journal of Industrial and Management Optimization, 6 (2010), 825846. doi: 10.3934/jimo.2010.6.825. Google Scholar 
[7] 
P. Q. Pan, A largestdistance pivot rule for the simplex algorithm, European Journal of Operational Research, 187 (2008), 393402. Google Scholar 
[8] 
X. J. Xu and Y. Y. Ye, A generalized homogeneous and selfdual algorithm for linear programming, Operations Research Letters, 17 (1995), 181190. doi: 10.1016/01676377(95)000022. Google Scholar 
[9] 
W. C. Yeh and H. W. Corley, A simple direct cosine simplex algorithm, Applied Mathematics and Computation, 214 (2009), 178186. doi: 10.1016/j.amc.2009.03.080. Google Scholar 
show all references
References:
[1] 
H. Arsham, A hybrid gradient and feasible direction pivotal solution algorithm for general linear programs, Applied Mathematics and Computation, 188 (2007), 596611. Google Scholar 
[2] 
H. Arsham, T. Damij and J. Grad, An algorithm for simplex tableau reduction: the pushtopull solution strategy, Applied Mathematics and Computation, 137 (2003), 525547. Google Scholar 
[3] 
E. Barnes, V. Chen, B. Gopalakrishnan and E. L. Johnson, A leastsquares primaldual algorithm for solving linear programming problems, Operations Research Letters, 30 (2002), 289294. doi: 10.1016/S01676377(02)001633. Google Scholar 
[4] 
G. B. Dantzig, "Linear Programming and Extensions," Princeton University Press, Princeton, N. J., 1963. Google Scholar 
[5] 
N. Karmarkar, A new polynomialtime algorithm for linear programming, Combinatorica, 4 (1984), 373395. doi: 10.1007/BF02579150. Google Scholar 
[6] 
Y. Liu, An exterior point linear programming method based on inclusive normal cones, Journal of Industrial and Management Optimization, 6 (2010), 825846. doi: 10.3934/jimo.2010.6.825. Google Scholar 
[7] 
P. Q. Pan, A largestdistance pivot rule for the simplex algorithm, European Journal of Operational Research, 187 (2008), 393402. Google Scholar 
[8] 
X. J. Xu and Y. Y. Ye, A generalized homogeneous and selfdual algorithm for linear programming, Operations Research Letters, 17 (1995), 181190. doi: 10.1016/01676377(95)000022. Google Scholar 
[9] 
W. C. Yeh and H. W. Corley, A simple direct cosine simplex algorithm, Applied Mathematics and Computation, 214 (2009), 178186. doi: 10.1016/j.amc.2009.03.080. Google Scholar 
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