Traffic optimization in railroad networks using an algorithm mimicking an amoeba-like organism, Physarum plasmodium
被引:43
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作者:
Watanabe, Shin
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机构:
Waseda Univ, Dept Elect Engn & Biosci, Shinjuku Ku, Tokyo 1698555, JapanWaseda Univ, Dept Elect Engn & Biosci, Shinjuku Ku, Tokyo 1698555, Japan
Watanabe, Shin
[1
]
Tero, Atsushi
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机构:
Kyushu Univ, Fac Math, Nishi Ku, Fukuoka 8190395, Japan
PRESTO Japan Sci & Technol Agcy, Kawaguchi, Saitama 3320012, JapanWaseda Univ, Dept Elect Engn & Biosci, Shinjuku Ku, Tokyo 1698555, Japan
Tero, Atsushi
[2
,3
]
Takamatsu, Atsuko
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机构:
Waseda Univ, Dept Elect Engn & Biosci, Shinjuku Ku, Tokyo 1698555, JapanWaseda Univ, Dept Elect Engn & Biosci, Shinjuku Ku, Tokyo 1698555, Japan
Takamatsu, Atsuko
[1
]
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机构:
Nakagaki, Toshiyuki
[4
]
机构:
[1] Waseda Univ, Dept Elect Engn & Biosci, Shinjuku Ku, Tokyo 1698555, Japan
[2] Kyushu Univ, Fac Math, Nishi Ku, Fukuoka 8190395, Japan
[3] PRESTO Japan Sci & Technol Agcy, Kawaguchi, Saitama 3320012, Japan
[4] Future Univ Hakodate, Dept Complex & Intelligent Syst, Fac Syst Informat Sci, Hakodate, Hokkaido 0418655, Japan
Traffic optimization of railroad networks was considered using an algorithm that was biologically inspired by an amoeba-like organism, plasmodium of the true slime mold, Physarum polycephalum. The organism developed a transportation network consisting of a tubular structure to transport protoplasm. It was reported that plasmodium can find the shortest path interconnecting multiple food sites during an adaptation process (Nakagaki et al., 2001. Biophys. Chem. 92, 47-52). By mimicking the adaptation process a path finding algorithm was developed by Tero et al. (2007). In this paper, the algorithm is newly modified for applications of traffic distribution optimization in transportation networks of infrastructure such as railroads under the constraint that the network topology is given. Application of the algorithm to a railroad in metropolitan Tokyo, Japan is demonstrated. The results are evaluated using three performance functions related to cost, traveling efficiency, and network weakness. The traffic distribution suggests that the modified Physarum algorithm balances the performances under a certain parameter range, indicating a biological process. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
机构:
School of Computer and Information Sciences, Southwest University, Chongqing 400715, ChinaSchool of Computer and Information Sciences, Southwest University, Chongqing 400715, China
Gao, Cai
Zhang, Xiaoge
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机构:
School of Computer and Information Sciences, Southwest University, Chongqing 400715, ChinaSchool of Computer and Information Sciences, Southwest University, Chongqing 400715, China
Zhang, Xiaoge
Zhang, Yajuan
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机构:
School of Computer and Information Sciences, Southwest University, Chongqing 400715, ChinaSchool of Computer and Information Sciences, Southwest University, Chongqing 400715, China
Zhang, Yajuan
Deng, Yong
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机构:
School of Engineering, Vanderbilt University, TN 37235, United StatesSchool of Computer and Information Sciences, Southwest University, Chongqing 400715, China
Deng, Yong
[J].
Journal of Information and Computational Science,
2014,
11
(04):
: 1163
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1169