A linear bilevel programming model and two analytical solution methods (the Kth-best algorithm and mixed integer programming reformulation) for the continuous network design problem are presented on the basis of the multiorigin, single-destination, user-optimal dynamic traffic assignment (UO DTA) problem. From the test problem, it is shown that the bilevel formulation is more desirable than the two known single-level models based respectively on system-optimal and UO DTA. For the multiorigin, multidestination, larger-size problem, three metaheuristics that can produce solutions beyond local optimality are employed: simulated annealing (SA), genetic algorithm (GA), and random search (RS). These metaheuristics share the same functional evaluation: a simulation-based UO DTA that propagates traffic according to Daganzo's cell transmission model. From computational results, GA outperforms the others for all three test problems in terms of solution quality, convergence speed, and processor time, whereas SA and RS appear nondominated. It is also shown that the appropriate set of algorithm parameters is network-specific and should be recalibrated for each network to achieve the best results.
Dynamic Continuous Network Design Problem
Linear Bilevel Programming and Metaheuristic Approaches
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 1964 , 1 ; 104-117
01.01.2006
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Robust Dynamic Continuous Network Design Problem
Transportation Research Record | 2007
|Robust Dynamic Continuous Network Design Problem
Online Contents | 2007
|A quantum-inspired genetic algorithm for dynamic continuous network design problem
Taylor & Francis Verlag | 2009
|Dynamic Continuous Network Design Problem: Linear Bilevel Programming and Metaheuristic Approaches
Transportation Research Record | 2006
|Dynamic Continuous Network Design Problem: Linear Bilevel Programming and Metaheuristic Approaches
Online Contents | 2006
|