An Enhanced Network-Consistent Travel Speed Generation Scheme on Time-Dependent Shortest Path and Routing Problems

Yıldırım, Umman Mahir; Çatay, Bülent

doi:10.1109/tits.2020.3016387

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…In summary, in treating speed, most of the literature uses the step function to represent the change of vehicle speed without considering the problem of continuity of vehicle speed. Yildirim and Catay argued that because TDGVRP proposed in most of the literature cannot capture some real features of real road networks and therefore cannot be used well to solve the associated shortest path problem, the authors propose to use real-life road networks and velocity data to generate real velocity data and demonstrate its applicability in TDGVRP in their paper [26]. To address this problem, Elomri et al proposed that the vehicle speed during traffic congestion continuously changes according to a certain rule rather than uniform motion [27].…”

Section: Review Of the Literaturementioning

confidence: 99%

Optimization of Vehicle Paths considering Carbon Emissions in a Time-Varying Road Network

Fang

2022

Journal of Advanced Transportation

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Regarding the study of the time-dependent green vehicle path problem (TDGVRP), most of the literature uses the step function to represent the vehicle speed change in order to reduce the computation, ignoring the continuity of vehicle speed, which leads to the lack of accurate carbon emissions measurement. This study represents the vehicle speed variation as a continuous function to make the constructed model more consistent with the actual situation, in order to promote the reduction of carbon emissions generated in the logistics and distribution process, improve the greenhouse effect and ecological environment, and ultimately promote sustainable development. In this paper, a simulated annealing-genetic hybrid algorithm (GA-SA) is proposed to solve the constructed optimization model, and two sets of comparison experiments are designed. The experimental results show that compared with the two classical algorithms, the simulated annealing-genetic hybrid algorithm (GA-SA) has better solution performance, inherits the robustness and potential parallelism of the genetic algorithm, and has a higher practical value. Meanwhile, although the total driving distance of the vehicle path considering carbon emissions increases by 3.52 km, the carbon emission cost and the total cost decrease by 5.6% and 3.4%, respectively, which confirms that the path optimization model considering carbon emissions constructed in this study can not only play the role of restraining carbon emissions but also reduce the total distribution cost and the waste of resources. In this study, a continuous function is used to represent the vehicle speed variation, and two classical optimization algorithms (the genetic algorithm and simulated annealing algorithm) are combined and parameter-optimized, and certain innovations are made in the processing of vehicle speed and the solution algorithm. Finally, the effectiveness of the model and algorithm is verified by experiments.

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Section: Review Of the Literaturementioning

confidence: 99%

Optimization of Vehicle Paths considering Carbon Emissions in a Time-Varying Road Network

Fang

2022

Journal of Advanced Transportation

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“…Masalah umum yang sering muncul dan diselesaikan dengan teori graf yaitu Shortest Path Problem/SPP dengan solusi menemukan jalur terpendek melalui titik-titik tujuan yang akan ditentukan [6]. Jalur terpendek dan rute kendaraan yang bergantung pada waktu bergantung pada data pengujian yang realistis dan masuk akal untuk demonstrasi dan evaluasi kinerja [7]. Masalah dalam mencari jarak minimum dalam loop tertutup terhadap berbagai parameter tanpa harus pergi ke tempat yang sama lebih dari satu kali [8].…”

Section: Pendahuluanunclassified

Algoritma Generate and Test Untuk Optimalisasi Masalah Rute Perjalanan

2021

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The common of urban city problem is a traffic jam, and it is heavily affect the public transportation service quality. Many cities in tropical countries suffer of heavy traffic jam due to the populaition of motorbike. According to Central Java Province Government, in 2014 the population of motorcycle is 439.418 units with the ownership ratio at 0.75 unit/person. Solo is one of typical middle size city in Central Java, Indonesia. Solo suffers from traffic jam in particular time of the day and it affect the quality of service of batik solo as the mass transportation service in Surakarta. This research would like to help the community get the optimal travel route with the fastest time, especially at the busiest times. The method used is Generate and Test algorithm. This method is a combination of Depth First Search and Backtracking. This research is conducted to get information about the influence of traffic volume, service road level and traffic jam level toward the time needed for Batik Solo Trans to find the optimal route. There is a route that been selected to be the most optimal route by considering the factors that influence it and the algorithm applied

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SRNN-RSA: a new method to solving time-dependent shortest path problems based on structural recurrent neural network and ripple spreading algorithm

Yu,

Song

2024

Complex Intell. Syst.

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Influenced by external factors, the speed of vehicles in the traffic network is changing all the time, which makes the traditional static shortest route unable to meet the real logistics distribution needs. Considering that the existing research on time-dependent shortest path problems (TDSPP) do not include the topological information of the traffic network, it is unable to reflect the spatial and temporal dynamic characteristics of the traffic network during the vehicle travelling process and is unable to update to the changes of the vehicle speed in real time, and poor scalability. Therefore, we used the structural RNN (SRNN) model containing topological information of the road network is used to predict time-varying speeds in the traffic road network. We proposed an SRNN-RSA framework for solving the TDSPP problem, which achieves a synergistic evolution between the real-time vehicle speed change process and the RSA solving process, and the scalability of the proposed SRNN-RSA is demonstrated and validated using different real data. Compared with other algorithms, the results show that SRNN-RSA has the lowest error with the actual situation, which can balance the solution accuracy and calculation speed and is more consistent with the real traffic road network, with better stability and expandability.

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An Enhanced Network-Consistent Travel Speed Generation Scheme on Time-Dependent Shortest Path and Routing Problems

Cited by 6 publications

References 28 publications

Optimization of Vehicle Paths considering Carbon Emissions in a Time-Varying Road Network

Optimization of Vehicle Paths considering Carbon Emissions in a Time-Varying Road Network

Algoritma Generate and Test Untuk Optimalisasi Masalah Rute Perjalanan

SRNN-RSA: a new method to solving time-dependent shortest path problems based on structural recurrent neural network and ripple spreading algorithm

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