0/1 Knapsack Problem using Branch and Bound | Least Cost (LC) Search | DAA
In this video, we dive deep into the 0/1 Knapsack Problem using the Least Cost (LC) Branch and Bound approach. This is a crucial topic in the Design and Analysis of Algorithms (DAA) and is widely used for solving optimization problems.
What you will learn in this video:
✅ Understanding the 0/1 Knapsack Problem.
✅ How the Branch and Bound technique works.
✅ Difference between FIFO, LIFO, and Least Cost (LC) search.
✅ Step-by-step numerical example using the LC strategy.
✅ State Space Tree construction for Knapsack.
This tutorial is perfect for Computer Science students preparing for university exams (GATE, UGC NET) or anyone looking to master algorithmic strategies.
📌 Timestamps:
0:00 - Introduction to 0/1 Knapsack Problem
0:45 - What is Branch and Bound?
1:30 - Understanding Least Cost (LC) Search
3:00 - Step-by-Step Example Walkthrough
8:45 - State Space Tree Explanation
12:00 - Summary & Key Takeaways
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