(maxima.info)Functions and Variables for simplex

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80.2 Functions and Variables for simplex
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 -- Option variable: epsilon_lp
     Default value: '10^-8'

     Epsilon used for numerical computations in 'linear_program'.

     See also: 'linear_program'.

 -- Function: linear_program (<A>, <b>, <c>)

     'linear_program' is an implementation of the simplex algorithm.
     'linear_program(A, b, c)' computes a vector <x> for which 'c.x' is
     minimum possible among vectors for which 'A.x = b' and 'x >= 0'.
     Argument <A> is a matrix and arguments <b> and <c> are lists.

     'linear_program' returns a list which contains the minimizing
     vector <x> and the minimum value 'c.x'.  If the problem is not
     bounded, it returns "Problem not bounded!"  and if the problem is
     not feasible, it returns "Problem not feasible!".

     To use this function first load the 'simplex' package with
     'load(simplex);'.

     Example:

          (%i2) A: matrix([1,1,-1,0], [2,-3,0,-1], [4,-5,0,0])$
          (%i3) b: [1,1,6]$
          (%i4) c: [1,-2,0,0]$
          (%i5) linear_program(A, b, c);
                             13     19        3
          (%o5)            [[--, 4, --, 0], - -]
                             2      2         2

     See also: 'minimize_lp', 'scale_lp', and 'epsilon_lp'.

 -- Function: maximize_lp (<obj>, <cond>, [<pos>])

     Maximizes linear objective function <obj> subject to some linear
     constraints <cond>.  See 'minimize_lp' for detailed description of
     arguments and return value.

     See also: 'minimize_lp'.

 -- Function: minimize_lp (<obj>, <cond>, [<pos>])

     Minimizes a linear objective function <obj> subject to some linear
     constraints <cond>.  <cond> a list of linear equations or
     inequalities.  In strict inequalities '>' is replaced by '>=' and
     '<' by '<='.  The optional argument <pos> is a list of decision
     variables which are assumed to be positive.

     If the minimum exists, 'minimize_lp' returns a list which contains
     the minimum value of the objective function and a list of decision
     variable values for which the minimum is attained.  If the problem
     is not bounded, 'minimize_lp' returns "Problem not bounded!"  and
     if the problem is not feasible, it returns "Problem not feasible!".

     The decision variables are not assumed to be nonegative by default.
     If all decision variables are nonegative, set 'nonegative_lp' to
     'true'.  If only some of decision variables are positive, list them
     in the optional argument <pos> (note that this is more efficient
     than adding constraints).

     'minimize_lp' uses the simplex algorithm which is implemented in
     maxima 'linear_program' function.

     To use this function first load the 'simplex' package with
     'load(simplex);'.

     Examples:

          (%i1) minimize_lp(x+y, [3*x+y=0, x+2*y>2]);
                                4       6        2
          (%o1)                [-, [y = -, x = - -]]
                                5       5        5
          (%i2) minimize_lp(x+y, [3*x+y>0, x+2*y>2]), nonegative_lp=true;
          (%o2)                [1, [y = 1, x = 0]]
          (%i3) minimize_lp(x+y, [3*x+y=0, x+2*y>2]), nonegative_lp=true;
          (%o3)                Problem not feasible!
          (%i4) minimize_lp(x+y, [3*x+y>0]);
          (%o4)                Problem not bounded!

     See also: 'maximize_lp', 'nonegative_lp', 'epsilon_lp'.

 -- Option variable: nonegative_lp
     Default value: 'false'

     If 'nonegative_lp' is true all decision variables to 'minimize_lp'
     and 'maximize_lp' are assumed to be positive.

     See also: 'minimize_lp'.

 -- Option variable: scale_lp
     Default value: 'false'

     When 'scale_lp' is 'true', 'linear_program' scales its input so
     that the maximum absolute value in each row or column is 1.

 -- Variable: pivot_count_sx

     After 'linear_program' returns, 'pivot_count_sx' is the number of
     pivots in last computation.

 -- Variable: pivot_max_sx

     'pivot_max_sx' is the maximum number of pivots allowed by
     'linear_program'.