Pivot versus interior point methods: Pros and cons
暂无分享,去创建一个
[1] J. L. Nazareth. Computer solution of linear programs , 1987 .
[2] G. Sonnevend. An "analytical centre" for polyhedrons and new classes of global algorithms for linear (smooth, convex) programming , 1986 .
[3] Jacek Gondzio,et al. Implementation of Interior Point Methods for Large Scale Linear Programming , 1996 .
[4] Gautam Mitra,et al. Simplex algorithms , 1996 .
[5] E. Beale. Cycling in the dual simplex algorithm , 1955 .
[6] Tibor Illés,et al. A new and constructive proof of two basic results of linear programming , 2001 .
[7] H. M. Wagner. The dual simplex algorithm for bounded variables , 1958 .
[8] John A. Tomlin,et al. Implementing the Simplex Method for the Optimization Subroutine Library , 1992, IBM Syst. J..
[9] T. Terlaky. A convergent criss-cross method , 1985 .
[10] V. Klee,et al. HOW GOOD IS THE SIMPLEX ALGORITHM , 1970 .
[11] P. Wolfe. A Technique for Resolving Degeneracy in Linear Programming , 1963 .
[12] Stephen J. Wright. Primal-Dual Interior-Point Methods , 1997, Other Titles in Applied Mathematics.
[13] Hans Frenk,et al. High performance optimization , 2000 .
[14] James E. Ward,et al. Approaches to sensitivity analysis in linear programming , 1991 .
[15] Shuzhong Zhang,et al. Pivot rules for linear programming: A survey on recent theoretical developments , 1993, Ann. Oper. Res..
[16] Jiming Peng,et al. A New Class of Polynomial Primal-dual Methods for Linear and Semideenite Optimization , 1999 .
[17] Tamás Terlaky,et al. An easy way to teach interior-point methods , 2001, Eur. J. Oper. Res..
[18] Hans-Jakob Lüthi,et al. The existence of a short sequence of admissible pivots to an optimal basis in LP and LCP , 1997 .
[19] Knud D. Andersen,et al. The Mosek Interior Point Optimizer for Linear Programming: An Implementation of the Homogeneous Algorithm , 2000 .
[20] Robert G. Bland,et al. New Finite Pivoting Rules for the Simplex Method , 1977, Math. Oper. Res..
[21] Tamás Koltai,et al. The difference between the managerial and mathematical interpretation of sensitivity analysis results in linear programming , 2000 .
[22] Robert E. Bixby,et al. Progress in Linear Programming , 1993 .
[24] Katta G. Murty,et al. Operations Research: Deterministic Optimization Models , 1994 .
[25] Michael A. Saunders,et al. A practical anti-cycling procedure for linearly constrained optimization , 1989, Math. Program..
[26] G. Dantzig,et al. Notes on Linear Programming: Part 1. The Generalized Simplex Method for Minimizing a Linear Form under Linear Inequality Restraints , 1954 .
[27] M. J. D. Powell,et al. Nonlinear Programming—Sequential Unconstrained Minimization Techniques , 1969 .
[28] John E. Beasley. Advances in Linear and Integer Programming , 1996 .
[29] Roy E. Marsten,et al. Feature Article - Interior Point Methods for Linear Programming: Computational State of the Art , 1994, INFORMS J. Comput..
[30] A. J. Hoffman. Cycling in the Simplex Algorithm , 2003 .
[31] David P. Williamson,et al. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming , 1995, JACM.
[32] B. Jansen,et al. Sensitivity analysis in linear programming: just be careful! , 1997 .
[33] Elmer Earl. Branstetter,et al. The theory of linear programming , 1963 .
[34] A. Charnes. Optimality and Degeneracy in Linear Programming , 1952 .
[35] K. Fukuda,et al. On the finiteness of the criss-cross method , 1991 .
[36] Tam As Terlaky. An Easy Way to Teach Interior Point Methods , 1998 .
[37] András Prékopa,et al. On the Development of Optimization Theory , 1980 .
[38] Jiming Peng,et al. Self-Regular Proximities and New Search Directions for Linear and Semidefinite Optimization , 2000 .
[39] Jan Karel Lenstra,et al. History of mathematical programming : a collection of personal reminiscences , 1991 .
[40] Tamás Terlaky,et al. Criss-cross methods: A fresh view on pivot algorithms , 1997, Math. Program..
[41] C. E. Lemke,et al. The dual method of solving the linear programming problem , 1954 .
[42] Margaret H. Wright,et al. The interior-point revolution in constrained optimization , 1998 .
[43] James D. Currie. The complexity of the simplex algorithm , 1984 .
[44] Shuzhong Zhang,et al. New variants of finite criss-cross pivot algorithms for linear programming , 1999, Eur. J. Oper. Res..
[45] K. Borgwardt. The Simplex Method: A Probabilistic Analysis , 1986 .
[46] Nesa L'abbe Wu,et al. Linear programming and extensions , 1981 .
[47] Donald Goldfarb,et al. Steepest-edge simplex algorithms for linear programming , 1992, Math. Program..
[48] T Talaky,et al. Interior Point Methods of Mathematical Programming , 1997 .
[49] Narendra Karmarkar,et al. A new polynomial-time algorithm for linear programming , 1984, Comb..
[50] Yurii Nesterov,et al. Interior-point polynomial algorithms in convex programming , 1994, Siam studies in applied mathematics.
[51] Jean-Philippe Vial,et al. Theory and algorithms for linear optimization - an interior point approach , 1998, Wiley-Interscience series in discrete mathematics and optimization.