Initial data commit

Task/Knapsack-problem-Bounded/Python/knapsack-problem-bounded-3.py

@@ -0,0 +1,59 @@
+items = {
+	"sandwich":	(50,	60,	2),
+	"map": 		(9,	150,	1),
+	"compass": 	(13,	35,	1),
+	"water": 	(153,	200,	3),
+	"glucose": 	(15,	60,	2),
+	"tin": 		(68,	45,	3),
+	"banana": 	(27,	60,	3),
+	"apple": 	(39,	40,	3),
+	"cheese": 	(23,	30,	1),
+	"beer": 	(52,	10,	3),
+	"suntan cream": (11,	70,	1),
+	"camera": 	(32,	30,	1),
+	"t-shirt": 	(24,	15,	2),
+	"trousers": 	(48,	10,	2),
+	"umbrella": 	(73,	40,	1),
+	"w-trousers": 	(42,	70,	1),
+	"w-overcoat": 	(43,	75,	1),
+	"note-case": 	(22,	80,	1),
+	"sunglasses": 	(7,	20,	1),
+	"towel": 	(18,	12,	2),
+	"socks": 	(4,	50,	1),
+	"book": 	(30,	10,	2),
+}
+
+item_keys = list(items.keys())
+
+#cache: could just use memoize module, but explicit caching is clearer
+def choose_item(weight, idx, cache):
+    if idx < 0: return 0, []
+
+    k = (weight, idx)
+    if k in cache: return cache[k]
+
+    name, w, v, qty = item_keys[idx], *items[item_keys[idx]]
+    best_v, best_list = 0, []
+
+    for i in range(0, qty + 1):
+        wlim = weight - i * w
+        if wlim < 0: break
+
+        val, taken = choose_item(wlim, idx - 1, cache)
+        if val + i * v > best_v:
+            best_v = val + i * v
+            best_list = taken[:]
+            best_list.append((i, name))
+
+    cache[k] = [best_v, best_list]
+    return best_v, best_list
+
+
+v, lst = choose_item(400, len(items) - 1, {})
+w = 0
+for cnt, name in lst:
+    if cnt > 0:
+        print(cnt, name)
+        w = w + items[name][0] * cnt
+
+print("Total weight:", w, "Value:", v)