This document describes a project that proposes a hierarchical graph model called HEPV (Hierarchical Encoded Path View) to efficiently find optimal paths for transportation applications. The HEPV model partitions a large graph into smaller subgraphs and precomputes paths between border nodes to allow for on-demand optimal path retrieval. Algorithms are developed to create and maintain the HEPV structure and to retrieve optimal paths between any two nodes by searching partitions and an encoded supergraph. The project scope involves developing this hierarchical graph model, algorithms for path computation and precomputation, and a GUI for users to obtain optimal paths.

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Presented by……………
Ashwini More B8238586
Punam Nerkar B8238589
Ramola Nikam B8238591
Shradha Pidhekar B8238605
Hierarchical Optimization of
Optimal Path Finding for
Transportation Applications
SINHGAD COLLEGE OF ENGINEERING,
PUNE – 41
DEPARTMENT OF INFORMATION TECHNOLOGY

2. PROJECT DETAILS
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 Group No : 28
 Category : In house
 Project Area : Data Structures
 Project Platform : Windows, JAVA
Guided By…...
Prof. U.R.GODASE

3. AGENDA
 Introduction
 Literature Survey
 Problem Statement
 Project Scope
 Project Analysis
 Project Design
 Implementation(Algorithms)
 Project Plan
 Conclusions
 References
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4. INTRODUCTION
 Efficient path query
processing
 Study the problem in
the context of
automobile
navigation systems
 Precomputing
Technique were used
 Proposed HEPV
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5. LITERATURE SURVEY
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Sr.
no
Dijkstra Transitive
Closure
Hierarchical A* HEPV
1 On demand Precompute Both Precompute
and On demand
Both Precompute
and On demand
2 No
Fragments
No Fragments Fragments Fragments
3 No Optimality
Guaranteed
No Optimality
Guaranteed
No
Optimality
Guaranteed
Optimality
Guaranteed
4 Can’t handle
Large graph
Can handle
Huge graph
Can handle Huge
graph
Can handle Huge
graph

6. PROBLEM STATEMENT
 To find an optimal path for an
individual to travel in an
alien place such that
intermediate nodes are
revealed.
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7. PROJECT SCOPE
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 Propose a hierarchical graph
model
 Complete computation of paths
on-demand and precomputed
paths.

8. ENCODED PATH VIEW STRUCTURE
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9. ENCODED PATH VIEW STRUCTURE
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a
b c e
d2
3 4
c 2
4
6
PATH a-e

10. PROPOSED ALGORITHM : HEPV
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11. PROPOSED ALGORITHM : HEPV
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Border Nodes
Local Nodes

12. PROJECT ANALYSIS
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 Use Case Level 1 Diagram
Additional Diagrams

13. PROJECT DESIGN
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 Data Flow Diagram
 Entity Relationship Diagram
 Sequence Diagram
 State Transition Diagram

14. DATA FLOW DIAGRAM
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Create
Partition
Check
Source &
destination
Retrieve
Path
Extract
Border
Nodes
User
Create
supergraph
GUI
Source and
destination
Partition
Status of
Source and
Destination
Minimum
weight and path
Border
Nodes
Supergraph
Partition
Supergraph
Partition
Source &
destination

15. ENTITY RELATIONSHIP DIAGRAM
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PARTITION
SOURCE
HOP1
FLAT GRAPH
DEST WEIGHT
HOP
CREATE
SRC
DESTI
LWEIGHT
SUPERGRAPH
SOURCE1
DEST1
WEIGHT1
HOP2
PART NO
CREATE
* 1
*
1

16. SEQUENCE DIAGRAM
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sd Sequence Diagram Model
User System Partition Supergraph
Path Retrieval
alt
[if source/destination is border node]
[if source/destination is local node]
create_partition
get_border_node
check_link
get_min_wt_and_hop
encode_supergraph
enter_ source_destination
submit_source_destination
retrieve_path
retrieve_path
submit_optimal_path
display_optimal_path

17. STATE DIAGRAM
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stm State Diagram
Accepting source and
destination
Searching source and destination
Searching in partition
Searching in
Supergraph
Path retriev ed
Fi nal
start
not found
not found
found

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HEPV CREATION ALGORITHM

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3
7
4 5
1
5
1 6
2
4 4
5
1
HEPV CREATION ALGORITHM

20. HEPV CREATION ALGORITHM
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21. PATH RETRIEVAL ALGORITHM
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22. CASE 1
Source Node : Border Node
Destination Node: Border Node
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3
7
4 5
1
5
1 6
2
4 4
5
1

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CASE 2
Source Node : Border Node
Destination Node: Local Node
3
7
4 5
1
5
1 6
2
4 4
5
1

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CASE 3
Source Node : Local Node
Destination Node: Border Node
3
7
4 5
1
5
1 6
2
4 4
5
1

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CASE 4
Source Node : Local Node
Destination Node: Local Node
3
7
4 5
1
5
1 6
2
4 4
5
1

26. HEPV UPDATE ALGORITHM
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27. PROJECT PLAN
 Gantt Chart-I
 Gantt Chart-II
 Project Plan
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28. CONCLUSIONS
 Hierarchical graph model (HEPV) exploits path
retrieving strategies
 Algorithms are developed to create and maintain
HEPV
 Shortest path retrieval algorithm developed which
can be shown to be optimal
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29. REFERENCES
[1] Ning Jing, Yun-Wu Huang, Elke Rundensteiner,
“Hierarchical Optimization of Optimal Path Finding
for Transportation Applications.”,pp. 1-8.
[2] R. Agrawal, S. Dar and H. V. Jagadish, “Direct
Transitive Closure Algorithms: Design and
Performance Evaluation,” ACM TODS, Vol. 15, No.
3, Sep. 1990, pp. 427 – 458.
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30. REFERENCES
[3] R. Agrawal and H. V. Jagadish, “Hybrid Transitive
Closure Algorithms,” Proc. of the 16th VLDB Conf.,
1990, pp. 326 – 334.
[4] T. Cormen, C. Leiserson, and R. L. Rivest,
“Introduction to Algorithms,” The MIT Press, 1993.
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Thank You…