hello-algo/en/codes/javascript/chapter_dynamic_programming/unbounded_knapsack.js

64 lines
1.9 KiB
JavaScript

/**
* File: unbounded_knapsack.js
* Created Time: 2023-08-23
* Author: Gaofer Chou (gaofer-chou@qq.com)
*/
/* Complete knapsack: Dynamic programming */
function unboundedKnapsackDP(wgt, val, cap) {
const n = wgt.length;
// Initialize dp table
const dp = Array.from({ length: n + 1 }, () =>
Array.from({ length: cap + 1 }, () => 0)
);
// State transition
for (let i = 1; i <= n; i++) {
for (let c = 1; c <= cap; c++) {
if (wgt[i - 1] > c) {
// If exceeding the knapsack capacity, do not choose item i
dp[i][c] = dp[i - 1][c];
} else {
// The greater value between not choosing and choosing item i
dp[i][c] = Math.max(
dp[i - 1][c],
dp[i][c - wgt[i - 1]] + val[i - 1]
);
}
}
}
return dp[n][cap];
}
/* Complete Knapsack: Space-optimized dynamic programming */
function unboundedKnapsackDPComp(wgt, val, cap) {
const n = wgt.length;
// Initialize dp table
const dp = Array.from({ length: cap + 1 }, () => 0);
// State transition
for (let i = 1; i <= n; i++) {
for (let c = 1; c <= cap; c++) {
if (wgt[i - 1] > c) {
// If exceeding the knapsack capacity, do not choose item i
dp[c] = dp[c];
} else {
// The greater value between not choosing and choosing item i
dp[c] = Math.max(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[cap];
}
/* Driver Code */
const wgt = [1, 2, 3];
const val = [5, 11, 15];
const cap = 4;
// Dynamic programming
let res = unboundedKnapsackDP(wgt, val, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);
// Space-optimized dynamic programming
res = unboundedKnapsackDPComp(wgt, val, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);