Description Format Author(s) References See Also Examples
The data set that corresponds to Example 3-6 found in Ignizio (1976). These are examples of goal programming problems solved using the methods described by author.
Find
{\mathbf{x}'} = [ x_1, x_2, x_3, x_4 ] ,
{\mathbf{n}'} = [ n_1, n_2, n_3, n_4, n_5, n_6, n_7 ] and
{\mathbf{p}'} = [ p_1, p_2, p_3, p_4, p_5, p_6, p_7 ] that minimize
\mathbf{a} = [ (2 p_1), (n_2), (n_3) ]
The objectives are as follows
x_1 + x_2 + n_1 - p_1 = 50000
x_1 + n_2 - p_2 = 20000
x_2 + n_3 - p_3 = 5000
x_2 + n_4 - p_4 = 15000
x_3 + n_5 - p_5 = 10000
x_4 + n_6 - p_6 = 30000
0.06 x_1 + 0.05 x_2 + 0.08 x_3 + 0.07 x_4 + n_7 - p_7 = 4000
\mathbf{x}, \mathbf{n}, \mathbf{p} ≥ \mathbf{0}
The solution is {\mathbf{x}'} = [ 20000, 5000, 0, 25000] and
\mathbf{a} = [0, 0, 5000, 10800]
The data set is an R file that creates the coefficients matrix, the vector of target values and the data frame of achievement goals.
Frederick Novomestky fnovomes@poly.edu
Ignizio, J. P. (1976). Goal Programming and Extensions, Lexington Books.
1 2 | data( ignizio.example.3.6 )
soln <- llgp( coefficients, targets, achievements )
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Loading required package: lpSolve
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