TSP with Genetic Algorithm

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082236 박수진082275 민지아082303 장이현061645 송창호

Algorithm Term ProjectTraveling Salesman’s Problemwith Genetic Algorithm

1 TSP2 Genetic Algorithm3 Application Case4 GUI & Demonstration5 Q & A

Traveling Salesman’s Problem

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01 Traveling Salesman’s Problem

NP-hard

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02 Traveling Salesman’s Problem Solution

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02 Traveling Salesman’s Problem Solution

Dynamic ProgramingBrute Force AlgorithmGreedy AlgorithmGenetic AlgorithmSimulated Annealing AlgorithmAnt Colony Optimization Algo-rithmRiver Formation DynamicsThe Cross Entropy MethodTabu Search……

Solution List

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문서의 제목 7

Genetic Algorithm

8

01 Genetic Algorithm

John Holland ( 1929 ~ )

• Professor of Electrical Engineering and Computer Science at the University of Michi-gan

• Known as the father of genetic algorithms

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Genetic Algorithm01

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Genetic Algorithm Pseudo Code02

Procedure GAInitialize Population;Evaluate Population;While not (terminal condition satisfied)

doSelect chromosomes for next popula-

tionCrossover and Mutation;Evaluate Population;End whileEnd Procedure

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Genetic Algorithm – Initialize Popula-tion

03

A B C D E F G

C E F A G D B

Ran-dom

Number Population

0 A B D F G E C

1 B C G F E D A

2

3

4

5

….

Population Group

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Genetic Algorithm – Evaluate Popula-tion

04

Number Population Fitness

0 A B D F G E C 120

1 B C G F E D A 240

2 C E F A G D B 490

3 G A E C B D F 100

4 C B A F G D E 320

5 A D G E F B C 190

…. … …

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Genetic Algorithm – Select05

Roulette Se-lection

Population_1 > Population_2 > Population_3 > …

Population_2

Population_3

Population_1

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Genetic Algorithm – Crossover06

0 1 0 1 1 0 1

1 0 0 1 0 1 1

0 1 0 1 0 1 1

1 0 0 1 1 0 1

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Genetic Algorithm – Crossover06

B C G F E D A

C B E A D F G

B C G F D F G

C B E A E D A

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Genetic Algorithm – Crossover06

A B C D E F G

A C D E F G

A D E F G

A D E F

A D E

A D

A

B C G F E D A

2 C G F E D A

2 2 G F E D A2 2 5 F E D A

2 2 5 4 E D A

2 2 5 4 3 D A

2 2 5 4 3 2 A

2 2 5 4 3 2 1

2 2 5 4 3 2 1

B 2 5 4 3 2 1

B C 5 4 3 2 1B C G 4 3 2 1

B C G F 3 2 1

B C G F E 2 1

B C G F E D 1

B C G F E D A

A B C D E F G

A C D E F G

A D E F G

A D E F

A D E

A D

A

Encoding Decoding

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Genetic Algorithm – Crossover06

2 2 5 4 3 2 1

3 2 3 1 1 1 1

2 2 5 4 1 1 1

3 2 3 1 3 2 1

B C G F A D E

C B E A G F D

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Genetic Algorithm – Mutation07

B C G F E D A

B E G F C D A

문서의 제목 19

Application Case

Everland Shortest tour

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01 Application Case – Everland Shortest tour

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Visual Studio 2010Edit Plus 3.31

Naver Map API.Net Framework

4.0

C#, Javascript

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02 ISSUE

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?

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02 ISSUE

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02 ISSUE

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가내 수공업

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02 ISSUE

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Drawing Map Naver Map

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03 GUI & Demonstration

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Q & A

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감사합니다