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Prepared by:

Rohaini Binti Mohd Noor

(2005614785)

Supervised by:

Dr Nordin Bin Abu Bakar

Proposal of Final Year Project


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Project Title

To Solve the Traveling

Salesman Problem by

using SimulatedAnnealing.


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Project Aim

The aim is to find the minimum

cost and shortest path

between 20 cities for theTraveling Salesman Problem.


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Project Objectives

1. to study the concept inSimulated Annealing

Algorithm.

2. to apply the SimulatedAnnealing Algorithm infinding the minimum cost andthe shortest path.


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Problem Descriptions

Given a collection of cities and thecost of travel between each pairof them, the Traveling Salesman

Problem, or TSP is to find thecheapest way of visiting all of thecities. The travel costs aresymmetric in the sense thattraveling from city X to city Ycosts just as much as travelingfrom Y to X.


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Project Scope

This study will make use of 20selected cities in Peninsular Malaysiato evaluate the above algorithm. The

selected cities are starting from KualaLumpur, Petaling Jaya, Shah Alam,Klang, Kajang, Seremban, Melaka,Batu Pahat, Johor Bharu, Kuantan,Kota Bharu, Kuala Terengganu,Kangar, Kulim, Alor Setar,Butterworth, Georgetown, Taiping andIpoh.


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Basic Idea

of TSP

a

b

d

c

f

e

3

6

3

21

4

5

3

6

1

Find the shortest path

using Dijkstras Algorithm

Iteration a b c d e f u S

0 0 3 INF 6 INF INF {a}

1 0 3 INF(8) 6(4) INF(6) INF b {a,b}

2 0 3 8(5) 4 6(8) INF d {a,b,d}

3 0 0 5 4 6(7) INF(11) c {a,b,d,c}

4 0 3 5 4 6 11(9) e {a,b,d,c,e}

5 0 3 5 4 6 9 f {a,b,d,c,e,f}

Trace of Dijkstras Algorithm


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a

b

d

c

f

e

3

1

31

2

The result:


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Examples of Solved Techniques in

Traveling Salesman Problem

There are several examples of solved techniquesin TSP that have been done by researchers

but I only stated three of the techniques

to be discussed in this report.

Methods Authors

Very Greedy Crossover in a

Genetic Algorithm.

Bryant A. Julstrom.

Department of Computer

Science, St. Cloud State

University.

Branch and Bound

Algorithm.R. Dakin (1997).

Branch and Cut Algorithm.

D. Applegate, R.E. Bixby, V.

Chvatal, and W. Cook

(1998).


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Project

Framework


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Hardware and Software

Requirements

Minimum Requirement

Hardware:

Processor - Intel Pentium IV

RAM 512 MB Hard Disk 40GB

Printer

Software:

Windows XP Professional

NetBin 5.0 Microsoft Visual Studio C++ 6.0

Microsoft Office Word 2003

Microsoft Project 2003


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Expected Outcomes

This project will produce a prototypethat will find a minimum cost and thedistance of the travelling. It willexamine whether the Simulated

Annealing can produce good resultcompared to known method that havebeen done before.


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Future Work

As for this semester, I only focus on writingthe proposal for this project. The TravelingSalesman Problem will be developed on thenext semester.

To enhance the system, the scope of thisproject will be broadened (number of cities,evaluation criteria and SA parameters willbe changed accordingly).


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Conclusion

This particular study shows the interest of aTraveling Salesman Problem (TSP). This project willadapt Simulated Annealing Algorithm to generatequickly a good approximation of the sets of efficientsolutions.

The problem is to find the minimum cost andshortest distance of the traveling. The TSP willproduce the minimum distance and the cost of thedistance.

The Traveling Salesman Problem will be using C++language as the engine while the interface will beusing VetBin 5.0. The development of this projectwill be starting on the next semester.


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THE END

THANK YOU

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