A-M baby

Task/Knapsack-problem-Bounded/Go/knapsack-problem-bounded.go

@@ -0,0 +1,78 @@
+package main
+import "fmt"
+
+type Item struct {
+	name string
+	weight, value, qty int
+}
+
+type Solution struct {
+	v, w int
+	qty []int
+}
+
+var items = []Item {
+	{"map",			9,	150,	1},
+	{"compass",		13,	35,	1},
+	{"water",		153,	200,	2},
+	{"sandwich",		50,	60,	2},
+	{"glucose",		15,	60,	2},
+	{"tin",			68,	45,	3},
+	{"banana",		27,	60,	3},
+	{"apple",		39,	40,	3},
+	{"cheese",		23,	30,	1},
+	{"beer",		52,	10,	3},
+	{"suntancream",		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-overclothes",	43,	75,	1},
+	{"note-case",		22,	80,	1},
+	{"sunglasses",		7,      20,	1},
+	{"towel",		18,	12,	2},
+	{"socks",		4,      50,	1},
+	{"book",		30,	10,	2},
+}
+
+func choose(weight, pos int, cache map[string]*Solution) (int, int, []int) {
+	if pos < 0 || weight <= 0 {
+		return 0, 0, make([]int, len(items))
+	}
+
+	str := fmt.Sprintf("%d,%d", weight, pos)
+	if s, ok := cache[str]; ok {
+		return s.v, s.w, s.qty
+	}
+
+	best_v, best_i, best_w, best_sol := 0, 0, 0, []int(nil)
+
+	for i := 0; i * items[pos].weight <= weight && i <= items[pos].qty; i++ {
+		v, w, sol := choose(weight - i * items[pos].weight, pos - 1, cache)
+		v += i * items[pos].value
+		if v > best_v {
+			best_i, best_v, best_w, best_sol = i, v, w, sol
+		}
+	}
+
+	taken := make([]int, len(items))
+	copy(taken, best_sol)
+	taken[pos] = best_i
+	v, w := best_v, best_w + best_i * items[pos].weight
+
+	cache[str] = &Solution{v, w, taken}
+	return v, w, taken
+}
+
+func main() {
+	v, w, s := choose(400, len(items) - 1, make(map[string]*Solution))
+
+	fmt.Println("Taking:")
+	for i, t := range s {
+		if t > 0 {
+			fmt.Printf("  %d of %d %s\n", t, items[i].qty, items[i].name)
+		}
+	}
+	fmt.Printf("Value: %d; weight: %d\n", v, w)
+}