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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
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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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. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) 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)  
Keyword(1) Ant Colony Optimization  
Keyword(2) optimization  
Keyword(3) diversity  
Keyword(4) swarm intelligence  
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  
4th Author's Affiliation Tokushima University (Tokushima Univ.)
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Date Time 2018-08-08 15:50:00 
Presentation Time 25 
Registration for NLP 
Paper # IEICE-NLP2018-60 
Volume (vol) IEICE-118 
Number (no) no.174 
Page pp.39-42 
#Pages IEICE-4 
Date of Issue IEICE-NLP-2018-08-01 

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