RosettaCodeData/Task/Vogels-approximation-method/D/vogels-approximation-method.d

81 lines
2.6 KiB
D

void main() {
import std.stdio, std.string, std.algorithm, std.range;
enum K { A, B, C, D, E, X, Y, Z, W }
immutable int[K][K] costs = cast() //**
[K.W: [K.A: 16, K.B: 16, K.C: 13, K.D: 22, K.E: 17],
K.X: [K.A: 14, K.B: 14, K.C: 13, K.D: 19, K.E: 15],
K.Y: [K.A: 19, K.B: 19, K.C: 20, K.D: 23, K.E: 50],
K.Z: [K.A: 50, K.B: 12, K.C: 50, K.D: 15, K.E: 11]];
int[K] demand, supply;
with (K)
demand = [A: 30, B: 20, C: 70, D: 30, E: 60],
supply = [W: 50, X: 60, Y: 50, Z: 50];
immutable cols = demand.keys.sort().release;
auto res = costs.byKey.zip((int[K]).init.repeat).assocArray;
K[][K] g;
foreach (immutable x; supply.byKey)
g[x] = costs[x].keys.schwartzSort!(k => cast()costs[x][k]) //**
.release;
foreach (immutable x; demand.byKey)
g[x] = costs.keys.schwartzSort!(k=> cast()costs[k][x]).release;
while (g.length) {
int[K] d, s;
foreach (immutable x; demand.byKey)
d[x] = g[x].length > 1 ?
costs[g[x][1]][x] - costs[g[x][0]][x] :
costs[g[x][0]][x];
foreach (immutable x; supply.byKey)
s[x] = g[x].length > 1 ?
costs[x][g[x][1]] - costs[x][g[x][0]] :
costs[x][g[x][0]];
auto f = d.keys.minPos!((a,b) => d[a] > d[b])[0];
auto t = s.keys.minPos!((a,b) => s[a] > s[b])[0];
if (d[f] > s[t]) {
t = f;
f = g[f][0];
} else {
f = t;
t = g[t][0];
}
immutable v = min(supply[f], demand[t]);
res[f][t] += v;
demand[t] -= v;
if (demand[t] == 0) {
foreach (immutable k, immutable n; supply)
if (n != 0)
g[k] = g[k].remove!(c => c == t);
g.remove(t);
demand.remove(t);
}
supply[f] -= v;
if (supply[f] == 0) {
foreach (immutable k, immutable n; demand)
if (n != 0)
g[k] = g[k].remove!(c => c == f);
g.remove(f);
supply.remove(f);
}
}
writefln("%-(\t%s%)", cols);
auto cost = 0;
foreach (immutable c; costs.keys.sort().release) {
write(c, '\t');
foreach (immutable n; cols) {
if (n in res[c]) {
immutable y = res[c][n];
if (y != 0) {
y.write;
cost += y * costs[c][n];
}
}
'\t'.write;
}
writeln;
}
writeln("\nTotal Cost = ", cost);
}