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117 lines
4.2 KiB
Java
117 lines
4.2 KiB
Java
/**
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* File: knapsack.java
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* Created Time: 2023-07-10
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* Author: krahets (krahets@163.com)
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*/
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package chapter_dynamic_programming;
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import java.util.Arrays;
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public class knapsack {
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/* 0-1 knapsack: Brute-force search */
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static int knapsackDFS(int[] wgt, int[] val, int i, int c) {
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// If all items have been selected or knapsack has no remaining capacity, return value 0
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if (i == 0 || c == 0) {
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return 0;
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}
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// If exceeds knapsack capacity, can only choose not to put it in
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if (wgt[i - 1] > c) {
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return knapsackDFS(wgt, val, i - 1, c);
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}
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// Calculate the maximum value of not putting in and putting in item i
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int no = knapsackDFS(wgt, val, i - 1, c);
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int yes = knapsackDFS(wgt, val, i - 1, c - wgt[i - 1]) + val[i - 1];
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// Return the larger value of the two options
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return Math.max(no, yes);
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}
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/* 0-1 knapsack: Memoization search */
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static int knapsackDFSMem(int[] wgt, int[] val, int[][] mem, int i, int c) {
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// If all items have been selected or knapsack has no remaining capacity, return value 0
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if (i == 0 || c == 0) {
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return 0;
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}
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// If there's a record, return it directly
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if (mem[i][c] != -1) {
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return mem[i][c];
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}
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// If exceeds knapsack capacity, can only choose not to put it in
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if (wgt[i - 1] > c) {
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return knapsackDFSMem(wgt, val, mem, i - 1, c);
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}
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// Calculate the maximum value of not putting in and putting in item i
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int no = knapsackDFSMem(wgt, val, mem, i - 1, c);
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int yes = knapsackDFSMem(wgt, val, mem, i - 1, c - wgt[i - 1]) + val[i - 1];
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// Record and return the larger value of the two options
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mem[i][c] = Math.max(no, yes);
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return mem[i][c];
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}
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/* 0-1 knapsack: Dynamic programming */
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static int knapsackDP(int[] wgt, int[] val, int cap) {
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int n = wgt.length;
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// Initialize dp table
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int[][] dp = new int[n + 1][cap + 1];
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// State transition
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for (int i = 1; i <= n; i++) {
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for (int c = 1; c <= cap; c++) {
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if (wgt[i - 1] > c) {
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// If exceeds knapsack capacity, don't select item i
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dp[i][c] = dp[i - 1][c];
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} else {
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// The larger value between not selecting and selecting item i
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dp[i][c] = Math.max(dp[i - 1][c], dp[i - 1][c - wgt[i - 1]] + val[i - 1]);
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}
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}
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}
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return dp[n][cap];
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}
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/* 0-1 knapsack: Space-optimized dynamic programming */
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static int knapsackDPComp(int[] wgt, int[] val, int cap) {
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int n = wgt.length;
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// Initialize dp table
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int[] dp = new int[cap + 1];
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// State transition
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for (int i = 1; i <= n; i++) {
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// Traverse in reverse order
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for (int c = cap; c >= 1; c--) {
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if (wgt[i - 1] <= c) {
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// The larger value between not selecting and selecting item i
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dp[c] = Math.max(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
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}
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}
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}
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return dp[cap];
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}
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public static void main(String[] args) {
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int[] wgt = { 10, 20, 30, 40, 50 };
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int[] val = { 50, 120, 150, 210, 240 };
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int cap = 50;
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int n = wgt.length;
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// Brute-force search
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int res = knapsackDFS(wgt, val, n, cap);
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System.out.println("Maximum item value not exceeding knapsack capacity is " + res);
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// Memoization search
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int[][] mem = new int[n + 1][cap + 1];
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for (int[] row : mem) {
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Arrays.fill(row, -1);
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}
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res = knapsackDFSMem(wgt, val, mem, n, cap);
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System.out.println("Maximum item value not exceeding knapsack capacity is " + res);
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// Dynamic programming
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res = knapsackDP(wgt, val, cap);
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System.out.println("Maximum item value not exceeding knapsack capacity is " + res);
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// Space-optimized dynamic programming
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res = knapsackDPComp(wgt, val, cap);
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System.out.println("Maximum item value not exceeding knapsack capacity is " + res);
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}
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}
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