Algorithm

Fundamentals of algorithmic problem solving||Design and Analysis of Algorithm

Asymptotic Notations||Design and analysis of Algorithm

Dijkstra’s algorithm|| Greedy Technique || Design and Analysis of Algorithm

Lower – Bound Arguments – P, NP NP- Complete and NP Hard Problems.

Travelling Salesman Problem using Branch and Bound Method

Approximation Algorithms for NP Hard Problems – Travelling Salesman problem – Knapsack problem

Simplex method || ITERATIVE IMPROVEMENT || Design and analysis of Algorithm

MULTI STAGE GRAPH || Dynamic programming

LIFO Search and FIFO search Knapsack Problem || Branch and Bound

Approximation Algorithms for NP Hard Problems Travelling Salesman problem Knapsack problem

Container loading problem || Greedy Technique

Fundamentals of algorithmic problem solving||Design and Analysis of Algorithm

kruskal's Algorithm|| Greedy Technique Programming || Design and Analysis of Algorithm

The Simplex Method || ITERATIVE IMPROVEMENT|| Design And Analysis of Algorithm

Brute Force Assignment problem

Huffman Tree -Greedy Technique | Design and analysis of Algorithm

Divide and conquer - Multiplication of Large Integers

Coin changing problem using Dynamic programming|| Design and Analysis of Algorithm

Knapsack Problem using Greedy Technique

Backtracking – n Queen problem || Design And Analysis of Algorithm

Backtracking - HAMILTONION CIRCUIT PROBLEMS

Maximum Matching in Bipartite Graphs || ITERATIVE IMPROVEMENT || Design and Analysis of Algorithm

Prims Algorithm || Greedy Technique Programming- Design and Analysis of Algorithm

knapsack problem brute force

Subset Sum Problem - Backtracking

Dynamic programming – Principle of optimality