Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Evolutionary optimization of the public transit network. / Krylatov, Alexander Yu; Shirokolobova, Anastasiya P.
Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018. ed. / Klyuev Vitaly; Pyshkin Evgeny; Natalia Bogach. Association for Computing Machinery, 2018. p. 29-34 (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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TY - GEN
T1 - Evolutionary optimization of the public transit network
AU - Krylatov, Alexander Yu
AU - Shirokolobova, Anastasiya P.
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Nowadays public transit network design is highly urgent challenge in a field of road network analysis. The issue is known to be complex and cumbersome because of a huge number of factors that should be taken into consideration to cope with it. Transit network design is not limited just by topological optimization but requires consideration of such non-network parameters as transit vehicles fleet, frequency-settings, transit vehicle classes, etc. No wonder that the corresponding optimization problems appears to be NP-hard. Therefore available today approaches for transit network design handling actual-size road networks are all based on evolution or genetic algorithms. This paper is devoted to the case of public transit network design in real road network with 1280 actual bus stops. Methodological tools exploited to solve this problem are discussed, computational results are given.
AB - Nowadays public transit network design is highly urgent challenge in a field of road network analysis. The issue is known to be complex and cumbersome because of a huge number of factors that should be taken into consideration to cope with it. Transit network design is not limited just by topological optimization but requires consideration of such non-network parameters as transit vehicles fleet, frequency-settings, transit vehicle classes, etc. No wonder that the corresponding optimization problems appears to be NP-hard. Therefore available today approaches for transit network design handling actual-size road networks are all based on evolution or genetic algorithms. This paper is devoted to the case of public transit network design in real road network with 1280 actual bus stops. Methodological tools exploited to solve this problem are discussed, computational results are given.
KW - Evolution strategies
KW - Evolutionary optimization
KW - Public transport
KW - Transit networks design
UR - http://www.scopus.com/inward/record.url?scp=85058631611&partnerID=8YFLogxK
U2 - 10.1145/3274856.3274863
DO - 10.1145/3274856.3274863
M3 - Conference contribution
AN - SCOPUS:85058631611
T3 - ACM International Conference Proceeding Series
SP - 29
EP - 34
BT - Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018
A2 - Vitaly, Klyuev
A2 - Evgeny, Pyshkin
A2 - Bogach, Natalia
PB - Association for Computing Machinery
T2 - 3rd International Conference on Applications in Information Technology, ICAIT 2018
Y2 - 1 November 2018 through 3 November 2018
ER -
ID: 40971362