0/1 Knapsack Using Branch and Bound Algorithm | Artificial Intelligence | Explained in Hindi 🔥 | AI

The 0/1 Knapsack Problem using Branch and Bound is an optimization technique to find the maximum profit without exploring all 2^N possible subsets. Instead of a brute-force binary tree expansion (where every item either goes IN or OUT), Branch and Bound uses Upper Bound estimates to prune sub-trees that cannot exceed the best profit found so far. 📌 Core Mechanism 1. Preprocessing (Sort Items): Sort items in descending order of their value-to-weight ratio (\frac{v_i}{w_i}). This ensures that upper bounds are calculated as tightly as possible. 2. Calculating the Upper Bound (Fractional Relaxation): At any state-space node, compute the maximum potential profit assuming remaining capacity can be filled using fractional parts of subsequent items (Fractional Knapsack): 3. Pruning Strategy : •Infeasible Node: •Unpromising Node: So If you Want to know More About 0/1 Knapsack Then Watch Out Our Latest Video on our Official YouTube channel Learn Smart... learn Fast Do Subscribe to our Channel and Share with others #artificialintelligence #ai #aiplaylist #0/1knapsackusingbranchandboundalgorithm #0/1knapsack #algorithm #machinelearning #datastructures #quicklearning #quicklearnerswithsamandmush #learnsmartlearnfast #computerscience #cse #btech #mtech #vtu #engineering #educationalvideo #gatesmashers #abdulbari