Algorithms presentation

1. Maze Path Finding
Presented By
Saqlain Mustak Sagor (2016-3-60-015)
Md. Shanewaz Akib (2016-3-60-050)
Md. Sajjad Hossain (2016-3-60-055)
Department of Computer Science & Engineering

2.  Introduction
 Example
 Application
 Using Backtracking
 Advantage
 Disadvantage
Overview
Slide 2

3. The Backtracking is an algorithmic-technique to
solve a problem by an incremental way. It uses
recursive approach to solve the problems. We
can say that the backtracking is used to find all
possible combination to solve an optimization
problem.
Introduction to Backtracking
Slide 3

4.  Puzzles such as eight queens puzzle,
crosswords, verbal arithmetic and Peg Solitaire.
 Combinatorial optimization problems such as
parsing and the knapsack problem.
 Logic programming languages such as Icon,
Planner and Prolog, which use backtracking
internally to generate answers.
Example of Backtracking
Slide 5

5. • Optimization and tactical problems
• Constraints Satisfaction Problem
• Electrical Engineering
• Robotics
• Artificial Intelligence
• Genetic and bioinformatics Algorithm
• Materials Engineering
• Network Communication
• Solving puzzles and path
Application of Backtracking
Slide 6

6. When do we use Backtracking
Normally it is used when we are faced with a number of options and we
have to choose one option. After choice we have a new set of options.
The procedure is repeated over and over until a final state.
Conceptually, start from the ROOT of a TREE that has CHILDREN that are
good/bad. So we want to go to good leaf by starting with the root and
choose one of its children and we move until we reach the good leaf.
If we get a bad leaf, we "backtrack" to search a good leaf by revoking our
most choice and try out the next option, if we ran out of options, revoke
the choice and try another choice at that node, if still there is no good
leaf and we are at the root, then there is no "GOAL STATE".
So we use Backtracking for searching for a solution to a problem among
all available
Slide 4

7. Advantages:
 Comparison with the Dynamic Programming,
Backtracking Approach is more effective in some cases.
 In greedy Algorithm, getting the Global Optimal
Solution is a long procedure and depends on user
statements but in Backtracking It Can Easily getable
Disadvantages:
 Backtracking Approach is not efficient for solving
strategic Problem.
 The overall runtime of Backtracking Algorithm is
normally slow.
Slide 7

8. Slide 8

9. Slide 9

10. Slide 10

11. Thank You!