LEVEL OF KNOWLEDGE REQUIRED:
Problem Solving Attitude
OBJECTIVES OF COURSE:
The objective of the course is to expertise the student in writing, designing and analyzing the algorithm
to solve a problem .
Upon completion of this course the learners will be:
Able to understand the necessity of the algorithm design.
Able to write the algorithm to solve a problem.
Able to analyze the performance of the algorithm.
Unit - 1
Unit – 2
Unit – 3
Unit – 4
Unit – 5
development of the algorithm, performance analysis ,
development of the algorithm, performance analysis,
The general method, Knapsack problem, tree vertex
splitting job sequencing with deadlines, Optimal
merge patterns, minimum cost spanning trees.
The general method , multistage graphs , all pairs
shortest paths , single source shortest paths : general
weights , 0/1 Knapsack problem , the travelling
salesman problem . Basic Traversal and search
Techniques: Techniques for binary trees and graphs
connected Components and spanning trees.
The general method, the 8-queens problem, sum of
subsets, graph colouring.Branch–and Bound: The
method, 0/1 knapsack problem, travelling salesman
The course will be taught using interactive lecture method. The concepts will be adequately illustrated with
examples to make applications of theoretical concepts clear. Students will be required to develop the programs
for the problems and they have to take Assignments and Exercises.
EVALUATION OF GRADING:
Students will be evaluated based on the following 3 stages.
5.1 Internal Assessment
Mid Term Examination
End term Examination
WEIGHTAGE – 30%
Internal Assessment shall be done based on the following:
% of Weightage
Internal Assessment Record Sheet (including Mid Term Examination marks) will be displayed
on LMS at the end of semester i.e. last week of regular classroom teaching.
5.1.1 CLASS TESTS/QUIZZES: Two Class Tests based on descriptive type theoretical & numerical
questions and Two Quizzes based on objective type questions will be held; one class test and one quiz
atleast ten days before the Mid Term Examination and second class test and second quizatleast ten days
before the End Term Examination. Those who do not appear in Viva-Voce and quiz examinations shall
lose their marks.
The marks obtained by the students will be displayed on LMS a week before the start of Mid Term and
End Term Examinations respectively.
5.1.2 ASSIGNMENTS:After completion of each unit or in the mid of the unit,there will be home assignments
based on theory and numerical problems.Those who fail to submit the assignments by the due date shall
lose their marks.
The marks obtained by the students will be displayed on LMS after each submission and subsequent
5.1.3 GENERAL DISCIPLINE:Based on student’s regularity, punctuality, sincerity and behaviour in the
The marks obtained by the students will be displayed on LMS at the end of semester.
MID TERM EXAMINATION:
WEIGHTAGE – 20%
Mid Term examination shall be Two Hours duration and shall be a combination ofObjective, Short and
Long theory Questions.
Date of showing Mid Term Examination Answer Sheets: Oct. 30/Nov 1st,
WEIGHTAGE – 50%
End Term Examination shall be Three Hours duration and shall be a combination of Objective, Short
and Long theory/numerical Questions.
The overall marks obtained at the end of the semester comprising all the above three mentioned shall be
converted to a grade.
Students are required to have a minimum attendance of 75% in the subject. Students with less than the
stipulated percentage shall not be allowed to appear in the End Term Examination
DETAILED SESSION PLAN
Detail of References
1.1 Notion of algorithm
1.2 Algorithmic process
1.3 Algorithm Design and analysis cycle
1.4 Performance Metrics
1.6 Significance of Big
1.7 Randomized algorithms
UNIT-Divide & Conquer
2.1 General Method-Discussions
2.2 Binary Search Technique
2.3 Finding Maximum and MinimumMinimum overhead
2.4 Merge Sort,Quick sort
2.5 Selection sort,Insertion Sort
2.6 Strassen’s Matrix Multiplication
UNIT-IV Dynamic Programming
4.1 Genral method-Discussion,Multi
UNIT-III: The Greedy Method
3.1 General MethodDiscussion,Knapsack
3.2 Tree vertex splitting
3.3 Job Sequencing problems,optimal
3.4 Mimimum cost spanning tree-method
4.2 All pair shortest path,Single source
4.4 Basic traversal and search
4.5 Search strategies-Graphs and Trees
5.1 General method-Discussion
5.2 N queens problem
5.3 Sum of subsets, Graph colouring
5.4 Branch and bound Vs Backtracking
5.5 Knapsack,TSP,B& B strategies
Total Number of Sessions: 36
TEXT BOOK [T]:
1.Introduction to Design and Analysis of Algorithm by AnanyLevitin, Pearson.
1. Ref. 1: Algorithm by Coremen, PHI.