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Wyświetlanie 1-3 z 3
Tytuł:
Generalized route planning approach for hazardous materials transportation with equity consideration
Autorzy:
Chai, H.
He, R.-C.
Jia, X.-yan
Ma, Ch.-x
Dai, C.-jie
Powiązania:
https://bibliotekanauki.pl/articles/223759.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hazardous materials transportation
transportation
route optimization
risk equity
multi-objective optimization
NSGA-II algorithm
genetic algorithm
transport materiałów niebezpiecznych
materiały niebezpieczne
optymalizacja trasy
kapitał własny
optymalizacja wielokryterialna
algorytm NSGA-II
algorytm genetyczny
Opis:
Hazardous materials transportation should consider risk equity and transportation risk and cost. In the hazardous materials transportation process, we consider risk equity as an important condition in optimizing vehicle routing for the long-term transport of hazardous materials between single or multiple origin-destination pairs (O-D) to reduce the distribution difference of hazardous materials transportation risk over populated areas. First, a risk equity evaluation scheme is proposed to reflect the risk difference among the areas. The evaluation scheme uses standard deviation to measure the risk differences among populated areas. Second, a risk distribution equity model is proposed to decrease the risk difference among populated areas by adjusting the path frequency between O-D pairs for hazardous materials transportation. The model is converted into two sub models to facilitate decision-making, and an algorithm is provided for each sub model. Finally, we design a numerical example to verify the accuracy and rationality of the model and algorithm. The numerical example shows that the proposed model is essential and feasible for reducing the complexity and increasing the portability of the transportation process.
Źródło:
Archives of Transport; 2018, 46, 2; 33-46
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of vehicle stability loss due to strong crosswind gusts using web services in the route planning process
Autorzy:
Betkier, Igor
Mitkow, Szymon
Kijek, Magdalena
Powiązania:
https://bibliotekanauki.pl/articles/223957.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
crosswind
transportation planning
vehicle stability
web applications
route planning
Źródło:
Archives of Transport; 2019, 52, 4; 47-56
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Passenger’s routes planning in stochastic common-lines’ multi-modal transportation network through integrating Genetic Algorithm and Monte Carlo simulation
Autorzy:
Peng, Yong
Mo, Zhiyao
Liu, Song
Powiązania:
https://bibliotekanauki.pl/articles/1955092.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
stochastic networks
multimodal transportation
passengers’ route
genetic algorithm
Monte Carlo simulation
sieci stochastyczne
transport multimodalny
algorytm genetyczny
symulacja Monte Carlo
Opis:
In the urban transportation network, most passengers choose public transportation to travel. However, bad weather, accidents, traffic jams and other factors lead to uncertainty in transportation network. Besides, transport vehicles running on the same segments of routes and belonging to different modes or routes make the transportation network more complicated. In order to improve the efficiency of passenger’s travel, this paper aim to introducing an approach for optimizing passenger travel routes. This approach takes the travel cost and the number of transfers as constraints to finding the shortest total travel duration of passenger in urban transportation network. The running duration and dwell duration of the vehicles in the network are uncertain, and the vehicles are running according to the timetables. As transportation modes, bus, rail transit and walk are considered. In terms of methodological contribution, this paper combines Genetic Algorithm (GA) and Monte Carlo simulation to deal with optimization problem under stochastic conditions. This paper uses Monte Carlo simulation to simulate the running duration and dwell time of vehicles in different scenarios to deal with the uncertainty of the network. The shortest path of passenger’s travel is solved by GA. Two kinds of population management strategies including single population management strategy and multiple population management strategy are designed to guide the solution population evolving process. The two kinds of population management strategies of GA are tested in numerical example. The satisfactory convergence performance and efficiency of the model and algorithm is verified by the numerical example. The numerical example also demonstrated that the multiple population management strategy of GA can get better results in a shorter CPU time. At the same time, the influences of some significant variables on solution are performed. This paper is able to provide a scientific quantitative support to the path scheme selection under the influence of common-lines and timetables of different modes of transportation in stochastic urban multimodal transportation network.
Źródło:
Archives of Transport; 2021, 59, 3; 73-92
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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