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- W2077765257 abstract "A new approach is proposed for relaxing the computational complexity of the user equilibrium discrete network design problem (UE-DNDP), under deterministic traffic conditions, with a solution search procedure based on the selectorecombinative genetic algorithm (SGA). The SGA uses only selection and recombination operators rather than mutation. The UE-DNDP approach proposed in this study has a bilevel structure: the upper-level problem relates to the strategy of the network design authority, and the lower-level problem deals with network user behaviors. To solve the upper-level problem, the SGA is first used to create feasible network design solutions to the UE-DNDP by accounting for a budget constraint. Then the design authority selects the best network design strategy with minimum total system travel time (TSTT). Extensive experimental design and testing on GA operators and parameters are conducted to select the useful GA operators and parameters. For the lower-level problem, the best K-value concept is ..." @default.
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- W2077765257 date "2006-01-01" @default.
- W2077765257 modified "2023-09-23" @default.
- W2077765257 title "Selectorecombinative Genetic Algorithm to Relax Computational Complexity of Discrete Network Design Problem" @default.
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- W2077765257 doi "https://doi.org/10.3141/1964-11" @default.
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