remove old glpm files

glpm.py

@@ -1,22 +0,0 @@
-def col_all_zeros(ls, i, al=0):
-    return all(x[i] == al for x in ls)
-def row_all_zeros(ls, i, al=0):
-    return all(x == al for x in ls[i])
-def matrix(name, ls, default=0):
-    nonzero_cols = [i+1 for i in range(len(ls[0])) if not col_all_zeros(ls, i, default)]
-    nonzero_rows = [i+1 for i in range(len(ls)) if not row_all_zeros(ls, i, default)]
-    res = ""
-    for r in nonzero_rows:
-        res += "\n{:2d}".format(r)
-        for c in nonzero_cols:
-            res += " {:2d}".format(ls[r-1][c-1])
-    return param(name, res, " : " + " ".join("{:2d}".format(x) for x in nonzero_cols))
-
-def dict(name, thing, default=None):
-    fmt_key = lambda k: " ".join((str(x+1) for x in k)) if type(k) == tuple else k+1
-    return param(name, ", ".join(["{} {}".format(fmt_key(k), v) for k,v in thing.items() if v != default]))
-def param(name, val, middle=""):
-    val = str(val)
-    if "\n" in val:
-        val = val.replace("\n", "\n" + " " * (len(name) + 6))
-    return "param {}{} := {};".format(name, middle, val)

model.glpm

@@ -1,84 +0,0 @@
-/* Number of people */
-param P_count, integer, > 0;
-
-/* Number of jobs */
-param J_count, integer, > 0;
-
-/* Number of days */
-param D_count, integer, > 0;
-
-param WL, integer, > 0;
-param WH, integer, > 0;
-param ML, integer, > 0;
-
-set P := 1..P_count;
-set J := 1..J_count;
-set D := 1..D_count;
-
-/* aanwezigheid x workload for that day */
-param Costs{p in P}, integer, >= 0;
-
-/* Person p likes to solve jobs j */
-param L{p in P, j in J} default 0, binary;
-
-/* Person p hates to solve jobs j */
-param H{p in P, j in J} default 0, binary;
-
-/* Person p is capable to perform job j */
-param C{p in P, j in J} default 1, binary;
-
-/* How many jobs need to be done on what day */
-param R{d in D, j in J}, integer, >= 0;
-
-/* hardcoded */
-param Q{p in P, j in J, d in D}, default 0, binary;
-
-/* workload */
-param Wl{j in J}, integer, >= 0;
-
-param max_load{p in P, d in D}, default 1, integer;
-
-/* Person p is allocated to do job j on day d */
-var A{p in P, j in J, d in D}, binary;
-
-var error{p in P}, integer, >= 0;
-
-s.t. hardcode{p in P, j in J, d in D}: A[p,j,d] >= Q[p,j,d];
-
-/* A person only has one task per day, at most */
-s.t. max_load_person{p in P, d in D}: sum{j in J} A[p,j,d] <= max_load[p,d];
-
-/* A person has at least 1 task */
-s.t. min_load_person{p in P}: sum{j in J, d in D} A[p,j,d] >= 1;
-
-/* A person does not perform the same job on all days */
-s.t. duplicate_jobs{p in P, j in J}: sum{d in D} A[p,j,d] <= D_count-1;
-
-s.t. max_load_person_total{p in P}: (sum{d in D, j in J} A[p,j,d] * Wl[j]) <= ML;
-
-/* Each task is allocated */
-s.t. all_allocated{j in J, d in D}: sum{p in P} A[p,j,d] == R[d, j];
-
-/* A person only performs what (s)he is capable of */
-s.t. capability_person{p in P, j in J, d in D}: A[p,j,d] <= C[p,j];
-
-s.t. error_lt{p in P}: error[p] >= ((sum{j in J, d in D} A[p,j,d] * Wl[j]) - Costs[p]);
-s.t. error_gt{p in P}: error[p] >= Costs[p] - (sum{j in J, d in D} A[p,j,d] * Wl[j]);
-
-/* Maximize enjoyment */
-# minimize error_diff: sum{p in P} error[p];
-maximize enjoyment: (sum{p in P, d in D, j in J} A[p,j,d] * (L[p, j] * WL - H[p, j] * WH)) - sum{p in P} error[p];
-solve;
-
-printf "Sum %d\n", (sum{p in P, d in D, j in J} A[p,j,d] * (L[p, j] * WL - H[p, j] * WH));
-printf "p d j W l\n";
-printf ">>>>\n";
-printf{p in P, d in D, j in J : A[p,j,d] > 0} "%d %d %d %d %d\n", p, d, j, A[p,j,d] * (L[p, j] * WL - H[p, j] * WH), Wl[j];
-printf "<<<<\n";
-printf "workloads\n";
-printf "p l\n";
-printf{p in P} "%d %d\n", p, abs((sum{j in J, d in D : A[p,j,d] > 0} Wl[j]) - Costs[p]);
-printf "workload_dev: %d\n", sum{p in P} abs((sum{j in J, d in D : A[p,j,d] > 0} Wl[j]) - Costs[p])^2;
-
-
-end;