loading
Papers

Research.Publish.Connect.

Paper

Authors: Koya Ihara 1 ; Shohei Kato 2 ; Takehiko Nakaya 3 ; Tomoaki Ogi 3 and Hiroichi Masuda 3

Affiliations: 1 Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan ; 2 Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan, Frontier Research Institute for Information Science, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan ; 3 Shimizu Corporation, 2-16-1 Kyobashi, Chuo-ku, Tokyo 104-8370, Japan

ISBN: 978-989-758-350-6

Keyword(s): Constrained Combinatorial Optimization, Genetic Algorithm, Particle Swarm Optimization, Shield Tunneling.

Abstract: It is expected that artificial intelligence reduce labor and improve productivity of the shield tunneling, which is one of the tunnel construction method. In the planning process of the shield tunneling, segments of the tunnel are assigned along to the predetermined curve called the planning line. Conventionally, skilled engineers manually assign the segments to minimize the amount of gaps between each segment and the planning line. Nevertheless, we have only to reduce each gap less than a tolerance, and there is a demand to reduce the amount of soil excavated along to the segments. Handling the reducing gaps as constraints and reducing the amount of excavated soil as an objective, this paper addresses the segment assignment as a constrained combinatorial optimization problem. These constraints are severe, and the problem have an extremely narrow feasible region. To solve the problem we proposed e constrained discrete genetic algorithm (eDGA) and e constrained integer categorical part icle swarm optimization (eICPSO), adapting a constraint handling method called the e constrained method to the discrete genetic algorithm and the integer categorical particle swarm optimization. The effectiveness of the eDGA and eICPSO to the segment assignment is shown by the two-dimensional simulator experiment using real construction data. The experimental results show that the proposed method have a potential to find the segment assignment reducing the amount of excavated soil as compared to the conventional method (skilled engineer) while keeping the all gaps between segments and the planning line falling within the tolerance. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.228.21.186

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ihara, K.; Kato, S.; Nakaya, T.; Ogi, T. and Masuda, H. (2019). A PSO based Approach to Assign Segments for Reducing Excavated Soil in Shield Tunneling.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 328-336. DOI: 10.5220/0007407803280336

@conference{icaart19,
author={Koya Ihara. and Shohei Kato. and Takehiko Nakaya. and Tomoaki Ogi. and Hiroichi Masuda.},
title={A PSO based Approach to Assign Segments for Reducing Excavated Soil in Shield Tunneling},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={328-336},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007407803280336},
isbn={978-989-758-350-6},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A PSO based Approach to Assign Segments for Reducing Excavated Soil in Shield Tunneling
SN - 978-989-758-350-6
AU - Ihara, K.
AU - Kato, S.
AU - Nakaya, T.
AU - Ogi, T.
AU - Masuda, H.
PY - 2019
SP - 328
EP - 336
DO - 10.5220/0007407803280336

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.