FHR-NSGA-III: a hybrid many-objective optimizer for intercity multimodal timetable optimization considering travel mode choice
DOI10.1016/j.ins.2023.119654zbMath1525.90229OpenAlexW4386701191MaRDI QIDQ6074956
Jianjun Wu, Yingzi Feng, Jiandong Zhao, Zi-You Gao
Publication date: 19 October 2023
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2023.119654
hybrid many-objective evolutionary algorithmhypervolume (HV)integrated intercity transportationmultimodal timetable optimization problem (TOP)passenger travel mode choice
Numerical mathematical programming methods (65K05) Multi-objective and goal programming (90C29) Transportation, logistics and supply chain management (90B06) Deterministic scheduling theory in operations research (90B35)
Cites Work
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- Approximating the least hypervolume contributor: NP-hard in general, but fast in practice
- SMS-EMOA: multiobjective selection based on dominated hypervolume
- Choices of intercity multimodal passenger travel modes
- Robust train regulation for metro lines with stochastic passenger arrival flow
- Barzilai and Borwein's method for multiobjective optimization problems
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