MINOS

MINOS is a large-scale optimization system, for the solution of sparse linear and nonlinear programs. The objective function and constraints may be linear or nonlinear, or a mixture of both. The nonlinear functions must be smooth. Stable numerical methods are employed throughout. Features include a new basis package (for maintaining sparse LU factors of the basis matrix), automatic scaling of linear contraints, and automatic estimation of some or all gradients. Upper and lower bounds on the variables are handled efficiently. File formats for constraint and basis data are compatible with the industry MPS format. The source code is suitable for machines with a Fortran 66 or 77 compiler and at least 500K bytes of storage. (Source: http://plato.asu.edu)


References in zbMATH (referenced in 440 articles )

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  1. Lustig, Irvin J.: An analysis of an available set of linear programming test problems (1989)
  2. Moon, Sangwon: A profit-maximizing plant-loading model with demand fill-rate constraints (1989)
  3. Pang, Jong-Shi; Yu, Chang-Sung: A min-max resource allocation problem with substitutions (1989)
  4. Pardalos, P. M.: Parallel search algorithms in global optimization (1989)
  5. Ragsdale, Cliff; Stam, Antonie: A note on solving quadratic programs using mixed-integer programming (1989)
  6. Robinson, S. M.: Bundle-based decomposition: Conditions for convergence (1989)
  7. Talpaz, Hovav; Alexander, William P.; Shumway, C. Richard: Estimation of systems of equations subject to curvature constraints (1989)
  8. Tan, H. H.; Potts, R. B.: A discrete path/trajectory planner for robotic arms (1989)
  9. Bixby, Robert E.; Fourer, Robert: Finding embedded network rows in linear programs. I: Extraction heuristics (1988)
  10. Byrd, Richard H.; Schnabel, Robert B.; Shultz, Gerald A.: Parallel quasi-Newton methods for unconstrained optimization (1988)
  11. Dantzig, George B.; McAllister, Patrick H.; Stone, John C.: Formulating an objective for an economy (1988)
  12. Fang, S. C.; Peterson, E. L.; Rajasekera, J. R.: Controlled dual perturbations for posynomial programs (1988)
  13. Feijoo, B.; Meyer, R. R.: Piecewise-linear approximation methods for nonseparable convex optimization (1988)
  14. Gill, Philip E.; Murray, Walter; Saunders, Michael A.; Wright, Margaret H.: Recent developments in constrained optimization (1988)
  15. Goh, C. J.; Teo, K. L.: Control parametrization: a unified approach to optimal control problems with general constraints (1988)
  16. Nazareth, L.; Wets, R. J.-B.: Nonlinear programming techniques applied to stochastic programs with recourse (1988)
  17. Pardalos, P. M.: Linear complementarity problems solvable by integer programming (1988)
  18. Teo, K. L.; Goh, C. J.: On constrained optimization problems with nonsmooth cost functionals (1988)
  19. Trappey, Jui-Fen C.; Liu, C. Richard; Chang, Tien-Chien: Fuzzy nonlinear programming: Theory and application in manufacturing (1988)
  20. Fang, S. C.; Rajasekera, J. R.: A perturbation approach to the main duality theorem of quadratic geometric programming (1987)

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