Presolve: All rows and columns removed, though not optimal

Dear

I am trying to maximize Kendall's W (https://en.wikipedia.org/wiki/Kendall%27s_W) by adding an extra ranking (variable C). I already have an amount of dm rankings, each for alt alternatives. C has the properties that they are all integers from 1 to alt, which is ensured by the constraints using c. The variable ranking gives the sum for each alternative of their given ranking. The average of variable ranking is constant. I try to maximize the sum over all alternatives of the squared difference between ranking and average. However, presolve removes all rows and columns, though it sets C as a decreasing list from alt to 1. Model and output can be seen below. Any help would be very much appreciated!

Thanks in advance! Arnaut

m = gp.Model("qp")

    average = (dm+1)*(alt+1)/2

    totalRank = [0 for i in range(alt)]

    for i in range(alt):

        for a in range(dm):

            totalRank[i] += X[a][i]    

    M = alt+2

    tuplelistc = []

    for i in range(1, alt):

        for j in range(i + 1, alt+1):

            tuplelistc.append((i , j))

   

    coptions = tuplelist(tuplelistc)

    C = m.addVars(list(range(1, alt+1)), vtype=GRB.INTEGER, lb=1, ub = alt, name = "C")

    c = m.addVars(coptions, vtype=GRB.BINARY, name = "c")

    ranking = m.addVars(list(range(1,alt+1)), vtype=GRB.INTEGER, lb = dm + 1, ub = (dm+1)*alt, name = "ranking")

    m.addConstrs(ranking[i] == C[i] + totalRank[i-1] for i in range(1, alt+1))

    m.addConstrs(C[i] <= (C[j] - 0.5) + M*c[i,j] for i in range(1, alt) for j in range(i+1, alt+1))

    m.addConstrs(C[i] >= (C[j] + 0.5) + M*(1-c[i,j]) for i in range(1, alt) for j in range(i+1, alt+1))

    expr = QuadExpr()

    for i in range(1, alt+1):

        expr.add((ranking[i] - average)*(ranking[i] - average)*12/((dm+1)**2 * ((alt)**3 - (alt))))

       

    m.setObjective(expr, GRB.MAXIMIZE)

    m.optimize()

Optimize a model with 8649 rows, 4464 columns and 25854 nonzeros

Model fingerprint: 0x02f111b2

Model has 93 quadratic objective terms

Variable types: 0 continuous, 4464 integer (4278 binary)

Coefficient statistics:

  Matrix range     [1e+00, 1e+02]

  Objective range  [2e-04, 2e-04]

  QObjective range [6e-07, 6e-07]

  Bounds range     [1e+00, 7e+02]

  RHS range        [5e-01, 5e+02]

Presolve removed 8649 rows and 4464 columns

Presolve time: 0.00s

Presolve: All rows and columns removed

Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.02 work units)

Thread count was 1 (of 16 available processors)

Solution count 1: 0.542754

No other solutions better than 0.542754

Optimal solution found (tolerance 1.00e-04)

Best objective 5.427544656369e-01, best bound 5.427544656369e-01, gap 0.0000%

Presolve: All rows and columns removed, though not optimal

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