0 1 Knapsack Problem
📖 Scenario: You are packing a backpack for a hiking trip. You have a list of items, each with a weight and a value. Your backpack can only carry a limited weight. You want to choose items to maximize the total value without exceeding the weight limit.
🎯 Goal: Build a program that uses the 0 1 Knapsack algorithm to find the maximum value of items that fit in the backpack without exceeding the weight limit.
📋 What You'll Learn
Create arrays for item weights and values
Create an integer variable for the maximum weight capacity
Implement the 0 1 Knapsack dynamic programming logic
Print the maximum value that fits in the backpack
💡 Why This Matters
🌍 Real World
Packing efficiently for trips, resource allocation, budget management, and many optimization problems use the 0 1 Knapsack approach.
💼 Career
Understanding dynamic programming and optimization algorithms is important for software engineering, data science, and technical interviews.
Progress0 / 4 steps