The software contains some functions and drivers for solving LP problems of the form min c’x s.t Ax=b; x>=0 by a large neihghborhood infeasible predictor_corrector algorithm. It is based on Newton steps on the perturbed optimality system x.*s = m * 1 Ax = b c + A’lambda = s x>= 0 , s>=0 m-->0 The matrix A may be either full or sparse; computations are made accordingly. This is a software based on either SCILAB or matlab for solving large scale linear programming problems. It can be freely used for non commercial use.

References in zbMATH (referenced in 146 articles , 1 standard article )

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  1. Antczak, T.: Exactness property of the exact absolute value penalty function method for solving convex nondifferentiable interval-valued optimization problems (2018)
  2. Asllanaj, Fatmir; Addoum, Ahmad; Roche, Jean Rodolphe: Fluorescence molecular imaging based on the adjoint radiative transport equation (2018)
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  4. Delfino, A.; de Oliveira, W.: Outer-approximation algorithms for nonsmooth convex MINLP problems (2018)
  5. Jian, Jin-bao; Tang, Chun-ming; Shi, Lu: A feasible point method with bundle modification for nonsmooth convex constrained optimization (2018)
  6. Kolosnitsyn, A. V.: Computational efficiency of the simplex embedding method in convex nondifferentiable optimization (2018)
  7. Bajaj, Anuj; Hare, Warren; Lucet, Yves: Visualization of the $\varepsilon $-subdifferential of piecewise linear-quadratic functions (2017)
  8. Bonnans, J. Frédéric; Festa, Adriano: Error estimates for the Euler discretization of an optimal control problem with first-order state constraints (2017)
  9. Carlier, Guillaume; Dupuis, Xavier: An iterated projection approach to variational problems under generalized convexity constraints (2017)
  10. Chen, Xiang; Zhang, Xiong: An improved 2D MoF method by using high order derivatives (2017)
  11. Du, Yu; Ruszczyński, Andrzej: Rate of convergence of the bundle method (2017)
  12. Gilbert, Jean Charles: On the solution uniqueness characterization in the L1 norm and polyhedral gauge recovery (2017)
  13. Helou, Elias Salomão; Santos, Sandra A.; Simões, Lucas E. A.: On the local convergence analysis of the gradient sampling method for finite max-functions (2017)
  14. Kočvara, Michal; Outrata, Jiří V.: Inverse truss design as a conic mathematical program with equilibrium constraints (2017)
  15. Métivier, L.; Brossier, R.; Operto, S.; Virieux, J.: Full waveform inversion and the truncated Newton method (2017)
  16. Sala, Ramses; Baldanzini, Niccolò; Pierini, Marco: Global optimization test problems based on random field composition (2017)
  17. Shen, W. P.; Li, C.; Yao, J. C.: Approximate Cayley transform methods for inverse eigenvalue problems and convergence analysis (2017)
  18. Shi, Y.; Tuan, H. D.; Tuy, H.; Su, S.: Global optimization for optimal power flow over transmission networks (2017)
  19. Strekalovsky, Alexander S.: Global optimality conditions in nonconvex optimization (2017)
  20. Tong, Jun; Hu, Jian-Qiang; Hu, Jiaqiao: A computational algorithm for equilibrium asset pricing under heterogeneous information and short-sale constraints (2017)

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