updates

solver.py

@@ -63,8 +63,8 @@ def run_milp_model(data: dict):
     # Bench weights (Strictly trusts the payload dictionary)
     raw_bw = settings["bench_weights"]
     bench_weights = {int(k): float(v) for k, v in raw_bw.items()}
-    gk_bench_w = bench_weights.get(0, 0.03)
-    of_bench_ws = [bench_weights.get(i, 0.0) for i in [1, 2, 3]]
+    gk_bench_w = max(float(bench_weights.get(0, 0.03)), 0.0001)
+    of_bench_ws = [max(float(bench_weights.get(i, 0.0)), 0.0001) for i in [1, 2, 3]]
     avg_of_bench_w = sum(of_bench_ws) / len(of_bench_ws) if of_bench_ws else 0.05
 
     chip_gws: dict[int, str] = {}
@@ -344,16 +344,12 @@ def run_milp_model(data: dict):
             prob += pulp.lpSum(transfer_in[p][w] for p in players) == 0
 
         if chip == "fh":
-            # THE FIX: Decouple the unspent Free Hit money from the bank variable!
-
-            # 1. The Affordability Check: Ensure the new squad cost is <= total wealth
+            # THE FIX: Decouple the Free Hit budget from the continuous bank!
+            # The new squad cost must simply be <= total wealth.
             prob += itb[eff_prev] + pulp.lpSum(
                 fh_sell_price[p] * squad[p][eff_prev] for p in players
             ) >= pulp.lpSum(fh_sell_price[p] * squad[p][w] for p in players)
-
-            # 2. The Freeze Check: The real bank carries forward untouched.
-            # Because unspent money vanishes into the void instead of returning to itb[w],
-            # the solver gets 0 EV for hoarding it and is forced to spend every cent on the bench!
+            # The real bank is completely frozen and carries over untouched.
             prob += itb[w] == itb[eff_prev]
         else:
             prob += (