Solve linear programming problems
Linear programming solver
Finds the minimum of a problem specified by
f, x, b, beq, lb, and ub are vectors, and A and Aeq are matrices.
linprog
applies only to the solver-based approach. For a discussion
of the two optimization approaches, see First Choose Problem-Based or Solver-Based Approach.
x = linprog(f,A,b)
x = linprog(f,A,b,Aeq,beq)
x = linprog(f,A,b,Aeq,beq,lb,ub)
x = linprog(f,A,b,Aeq,beq,lb,ub,options)
x = linprog(problem)
[x,fval]
= linprog(___)
[x,fval,exitflag,output]
= linprog(___)
[x,fval,exitflag,output,lambda]
= linprog(___)
finds the minimum for x
= linprog(problem
)problem
, where
problem
is a structure described in Input Arguments.
Create the problem
structure by exporting a problem
from Optimization app, as described in Exporting Your Work. You can import a
problem
structure from an MPS file using
mpsread
. You can
also create a problem
structure from an
OptimizationProblem
object by using
prob2struct
.
[1] Dantzig, G.B., A. Orden, and P. Wolfe. “Generalized Simplex Method for Minimizing a Linear Form Under Linear Inequality Restraints.” Pacific Journal Math., Vol. 5, 1955, pp. 183–195.
[2] Mehrotra, S. “On the Implementation of a Primal-Dual Interior Point Method.” SIAM Journal on Optimization, Vol. 2, 1992, pp. 575–601.
[3] Zhang, Y., “Solving Large-Scale Linear Programs by Interior-Point Methods Under the MATLAB Environment.” Technical Report TR96-01, Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, MD, July 1995.
intlinprog
| mpsread
| optimoptions
| prob2struct
| quadprog