UNIT 1:
Fundamentals of Algorithmic Problem Solving
Empirical analysis - Mathematical analysis for Recursive Algorithms
Empirical analysis - Mathematical analysis for Non Recursive Algorithms
Asymptotic Notations and their properties
Mathematical Analysis of Non - Recursive Algorithms
Mathematical Analysis of Recursive Algorithms
UNIT 2:
Brute Force – Computing an – String Matching
Closest-Pair and Convex-Hull Problems
Closest-Pair and Convex-Hull Problems
Exhaustive Search - Travelling Salesman Problem
Knapsack Problem - Assignment problem
Multiplication of Large Integers – Closest-Pair and Convex - Hull Problems.
UNIT 3:
Dynamic programming – Principle of optimality - Coin changing problem
Computing a Binomial Coefficient – Floyd‘s algorithm –
Optimal Binary Search Trees
Knapsack Problem and Memory functions
Greedy Technique – Container loading problem -
Optimal Merge pattern - Huffman Trees
UNIT 4:
The Simplex Method - Geometric Interpretation of Linear Programming
Maximum Matching in Bipartite Graphs
UNIT 5:
- P, NP NP- Complete and NP Hard Problems
Backtracking – n-Queen problem
Hamiltonian Circuit Problem
Branch and Bound – LIFO Search and FIFO search - Assignment problem –
Traveling Salesman Problem
Approximation Algorithms for NP-Hard Problems – Travelling Salesman problem