Weighted vertex cover (as linear programming) in R with the ROI package

Question

I'm trying to solve an instance of the weighted vertex cover problem using R for homework and I can't seem to get it right. I'm using the ROI package (could just as well use linprog).

The instance looks like this:

Edges:
A-B,    A-C,    A-G,
B-C,    B-D,    B-E,    B-G,
C-E,    C-F,
D-F,
E-G,
F-H,    F-I,
G-H

Weights:
A - 10,
B - 7,
C - 4,
D - 7,
E - 12,
F - 25,
G - 27,
H - 3,
I - 9

My code is:

    #                                    a  b  c  d  e  f  g  h  i
    constraints <- L_constraint(matrix(c(1, 1, 0, 0, 0, 0, 0, 0, 0, # a b
                                         1, 0, 1, 0, 0, 0, 0, 0, 0, # a c
                                         1, 0, 0, 0, 0, 0, 1, 0, 0, # a g
                                         0, 1, 1, 0, 0, 0, 0, 0, 0, # b c
                                         0, 1, 0, 1, 0, 0, 0, 0, 0, # b d
                                         0, 1, 0, 0, 1, 0, 0, 0, 0, # b e
                                         0, 1, 0, 0, 0, 0, 1, 0, 0, # b g
                                         0, 0, 1, 0, 1, 0, 0, 0, 0, # c e
                                         0, 0, 1, 0, 0, 1, 0, 0, 0, # c f
                                         0, 0, 0, 1, 0, 1, 0, 0, 0, # d f
                                         0, 0, 0, 0, 1, 0, 1, 0, 0, # e g
                                         0, 0, 0, 0, 0, 1, 0, 1, 0, # f h
                                         0, 0, 0, 0, 0, 1, 0, 0, 1, # f i
                                         0, 0, 0, 0, 0, 0, 1, 1, 0, # g h
                                         # end of u + v >= 1
                                         1, 0, 0, 0, 0, 0, 0, 0, 0,
                                         0, 1, 0, 0, 0, 0, 0, 0, 0,
                                         0, 0, 1, 0, 0, 0, 0, 0, 0,
                                         0, 0, 0, 1, 0, 0, 0, 0, 0,
                                         0, 0, 0, 0, 1, 0, 0, 0, 0,
                                         0, 0, 0, 0, 0, 1, 0, 0, 0,
                                         0, 0, 0, 0, 0, 0, 1, 0, 0,
                                         0, 0, 0, 0, 0, 0, 0, 1, 0,
                                         0, 0, 0, 0, 0, 0, 0, 0, 1,
                                         # end of u >= 0
                                         1, 0, 0, 0, 0, 0, 0, 0, 0,
                                         0, 1, 0, 0, 0, 0, 0, 0, 0,
                                         0, 0, 1, 0, 0, 0, 0, 0, 0,
                                         0, 0, 0, 1, 0, 0, 0, 0, 0,
                                         0, 0, 0, 0, 1, 0, 0, 0, 0,
                                         0, 0, 0, 0, 0, 1, 0, 0, 0,
                                         0, 0, 0, 0, 0, 0, 1, 0, 0,
                                         0, 0, 0, 0, 0, 0, 0, 1, 0,
                                         0, 0, 0, 0, 0, 0, 0, 0, 1),
                                         # end of u <= 1
                                       ncol = 9), # matrix
                                dir = c(rep(">=", 14+9), rep("<=", 9)),
                                rhs = c(rep(1, 14), rep(0, 9), rep(1, 9))) # L_constraint

    objective <- L_objective(c(10, 7, 4, 7, 12, 25, 27, 3, 9))

    problem <- OP(objective, constraints, rep("C", 9),
                  maximum = FALSE)

    solution <- ROI_solve(problem, solver = "glpk")

The result is No solution found. I don't know what I'm doing wrong, but it may just as well be something obvious. Can't get my head around it -- a solution should always exist, even if it takes all the vertices (i. e. all variables are >= 0.5).

If it matters, I'm on Arch Linux running R from the repositories (ver. 2.14) and installed the packages via install.packages("...").

Thanks!

Answer 1

Okay, solved it. The problem was that I didn't add byrows = TRUE to the matrix definition. In addition I changed ncol = 9 into nrow = .... Apparently the matrix() function did not work as I expected.