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

114 lines
3.6 KiB
JavaScript

/**
* File: knapsack.js
* Created Time: 2023-08-23
* Author: Gaofer Chou (gaofer-chou@qq.com)
*/
/* 0-1 Knapsack: Brute force search */
function knapsackDFS(wgt, val, i, c) {
// If all items have been chosen or the knapsack has no remaining capacity, return value 0
if (i === 0 || c === 0) {
return 0;
}
// If exceeding the knapsack capacity, can only choose not to put it in the knapsack
if (wgt[i - 1] > c) {
return knapsackDFS(wgt, val, i - 1, c);
}
// Calculate the maximum value of not putting in and putting in item i
const no = knapsackDFS(wgt, val, i - 1, c);
const yes = knapsackDFS(wgt, val, i - 1, c - wgt[i - 1]) + val[i - 1];
// Return the greater value of the two options
return Math.max(no, yes);
}
/* 0-1 Knapsack: Memoized search */
function knapsackDFSMem(wgt, val, mem, i, c) {
// If all items have been chosen or the knapsack has no remaining capacity, return value 0
if (i === 0 || c === 0) {
return 0;
}
// If there is a record, return it
if (mem[i][c] !== -1) {
return mem[i][c];
}
// If exceeding the knapsack capacity, can only choose not to put it in the knapsack
if (wgt[i - 1] > c) {
return knapsackDFSMem(wgt, val, mem, i - 1, c);
}
// Calculate the maximum value of not putting in and putting in item i
const no = knapsackDFSMem(wgt, val, mem, i - 1, c);
const yes =
knapsackDFSMem(wgt, val, mem, i - 1, c - wgt[i - 1]) + val[i - 1];
// Record and return the greater value of the two options
mem[i][c] = Math.max(no, yes);
return mem[i][c];
}
/* 0-1 Knapsack: Dynamic programming */
function knapsackDP(wgt, val, cap) {
const n = wgt.length;
// Initialize dp table
const dp = Array(n + 1)
.fill(0)
.map(() => Array(cap + 1).fill(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 - 1][c - wgt[i - 1]] + val[i - 1]
);
}
}
}
return dp[n][cap];
}
/* 0-1 Knapsack: Space-optimized dynamic programming */
function knapsackDPComp(wgt, val, cap) {
const n = wgt.length;
// Initialize dp table
const dp = Array(cap + 1).fill(0);
// State transition
for (let i = 1; i <= n; i++) {
// Traverse in reverse order
for (let c = cap; c >= 1; c--) {
if (wgt[i - 1] <= c) {
// 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 = [10, 20, 30, 40, 50];
const val = [50, 120, 150, 210, 240];
const cap = 50;
const n = wgt.length;
// Brute force search
let res = knapsackDFS(wgt, val, n, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);
// Memoized search
const mem = Array.from({ length: n + 1 }, () =>
Array.from({ length: cap + 1 }, () => -1)
);
res = knapsackDFSMem(wgt, val, mem, n, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);
// Dynamic programming
res = knapsackDP(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 = knapsackDPComp(wgt, val, cap);
console.log(`不超过背包容量的最大物品价值为 ${res}`);