Application of multiple-population genetic algorithm in optimizing the train-set circulation plan problem
DOI10.1155/2017/3717654zbMath1373.90022OpenAlexW2734115662WikidataQ59142890 ScholiaQ59142890MaRDI QIDQ1674899
Jiawei Wu, Yu Zhou, Zhuo Yang, Yun Wang, Lei-shan Zhou
Publication date: 26 October 2017
Published in: Complexity (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2017/3717654
additional complexitymultiple-population genetic algorithm (MPGA)nondeterministic polynomial hard (NP-hard)rolling stock scheduling (RSS)train-set circulation optimization modeltrain-set circulation plan problem (TCPP)
Transportation, logistics and supply chain management (90B06) Approximation methods and heuristics in mathematical programming (90C59) Complexity and performance of numerical algorithms (65Y20)
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Cites Work
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- Improving robustness of rolling stock circulations in rapid transit networks
- Robust rolling stock in rapid transit networks
- Maintenance routing for train units: the interchange model
- Crew pairing at Air France
- The aircraft rotation problem
- The asymmetric traveling salesman problem with replenishment arcs
- A computational study of Benders decomposition for the integrated aircraft routing and crew scheduling problem
- Circulation of railway rolling stock: a branch-and-price approach
- A rolling stock circulation model for combining and splitting of passenger trains
- Solving a real-world train-unit assignment problem
- The Four-Day Aircraft Maintenance Routing Problem
- A Benders Decomposition Approach for the Locomotive and Car Assignment Problem
- Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling
- The Aircraft Maintenance Routing Problem
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