Paper Abstract and Keywords |
Presentation |
2018-08-08 15:50
Ant Colony Optimization for High Accuracy of Solutions Ken Kamiyotsumoto (Tokushima Univ.), Thomas Ott (ZHAW), Yoko Uwate, Yoshifumi Nshio (Tokushima Univ.) NLP2018-60 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recently, nature-inspired metaheuristic optimization algorithms such as Ant Colony Optimization
(ACO) is developed. ACO is based on the feeding behavior of ant herds. In this study, We propose a new ACO in which the pheromone’s reaction improves on increasing at the number of repetition for Traveling Salesman Problem (TSP). The standard ACO has constant pheromone’s reaction. However, the pheromone’s reaction of the propose method has changing state and constant state. We compare the solution with ACO and the proposed method.
We find optimal rate of repetition times of changing pheromone’s reaction. Then, We investigate characteristic of algorithm according to the change in the rate of repetitions. Average of solutions that ACO has two states is smaller than average of solutions that ACO has only changing state. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Ant Colony Optimization / optimization / diversity / swarm intelligence / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 174, NLP2018-60, pp. 39-42, Aug. 2018. |
Paper # |
NLP2018-60 |
Date of Issue |
2018-08-01 (NLP) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NLP2018-60 |
Conference Information |
Committee |
NLP |
Conference Date |
2018-08-08 - 2018-08-09 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Saiwai-cho Campus, Kagawa Univ. |
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(See Japanese page) |
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etc. |
Paper Information |
Registration To |
NLP |
Conference Code |
2018-08-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Ant Colony Optimization for High Accuracy of Solutions |
Sub Title (in English) |
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Keyword(1) |
Ant Colony Optimization |
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optimization |
Keyword(3) |
diversity |
Keyword(4) |
swarm intelligence |
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1st Author's Name |
Ken Kamiyotsumoto |
1st Author's Affiliation |
Tokushima University (Tokushima Univ.) |
2nd Author's Name |
Thomas Ott |
2nd Author's Affiliation |
Zurich University of Applied Sciences (ZHAW) |
3rd Author's Name |
Yoko Uwate |
3rd Author's Affiliation |
Tokushima University (Tokushima Univ.) |
4th Author's Name |
Yoshifumi Nshio |
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Tokushima University (Tokushima Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-08-08 15:50:00 |
Presentation Time |
25 minutes |
Registration for |
NLP |
Paper # |
NLP2018-60 |
Volume (vol) |
vol.118 |
Number (no) |
no.174 |
Page |
pp.39-42 |
#Pages |
4 |
Date of Issue |
2018-08-01 (NLP) |
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