A Fissile Ripple Spreading Algorithm to Solve Time-Dependent Vehicle Routing Problem via Coevolutionary Path Optimization

Xu, Wenlong; Li, Jiajun

doi:10.1155/2020/8815983

Cited by 7 publications

(6 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Liu [14] established the sum of the carbon emission cost, transportation cost, penalty cost for exceeding the time window, and the damage cost of the cold chain cargo as the objective function and established a route optimization model of cold chain container multimodal transportation. Xu and Li [15] researched the time-dependent vehicle routing problem and proposed an unconventional path optimization approach, known as the fssile ripple spreading algorithm (FRSA). Liu and Zhang [16] considered the time dependence of link weights and optimized the shortest path within a time window with time-dependent driving risk.…”

Section: Literature Reviewmentioning

confidence: 99%

Study on the Shortest Reliable Path of Stochastic Time-Dependent Transportation Networks considering Waiting Time at Signalized Intersections

Sun,

Li,

Liu

2023

Journal of Advanced Transportation

View full text Add to dashboard Cite

Theoretical research is conducted on finding the shortest path with stochastic and time-dependent characteristics of link travel time in urban road networks. Considering the influence of signalized intersections on travel time, the research first presents a function of waiting time at signalized intersections and analyzes its characteristics. Then, considering the reliability of travel time, the travel time model under the min-max theorem is established, and a mathematical proof that the stochastic time-dependent traffic networks can be reduced to a deterministic time-dependent network is presented by using the first mathematical induction. Finally, based on analyzing the characteristics of the shortest path and minimum travel time, which vary with the start time, we propose solving the shortest path problem with a shortest path algorithm based on Dijkstra’s algorithm that takes the waiting time at signalized intersections into consideration. The research results showed that the algorithm proposed in this study does not depend on the acquisition of the probability distribution of travel time compared with the traditional algorithm. The range of uncertain travel time can be derived from historical data and travelers’ experiences, and the obtained shortest path has more robust time reliability.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Study on the Shortest Reliable Path of Stochastic Time-Dependent Transportation Networks considering Waiting Time at Signalized Intersections

Sun,

Li,

Liu

2023

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…In addition, Xu and Li proposed an unconventional path optimization method for dynamic road conditions and traffic congestion and a fission ripple diffusion algorithm based on coevolutionary path optimization to solve the problem [20]. Liu et al considered the effect of vehicle travel speed on carbon emissions, proposed a calculation method across the time domain and a method to avoid traffic congestion during peak hours, and designed an improved ant colony algorithm to solve this problem [21].…”

Section: Review Of the Literaturementioning

confidence: 99%

“…Fan et al proposed that the relationship between vehicle speed (v) and time (t) during peak hours is V � ɑSin (yt) + δ (where ɑ, y, and δ are coefficients related to road conditions) [10,20]. Franceschetti et al argued that the vehicle travel process can be divided into normal and congested periods according to whether the traffic is congested or not, and the vehicle speed in different periods is different, but all are in uniform motion [23][24][25].…”

Section: Vehicle Speed Processingmentioning

confidence: 99%

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

Fang

2022

Journal of Advanced Transportation

View full text Add to dashboard Cite

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.

show abstract

“…However, the dynamic routing environment and traffic congestions have made it challenging to make the actual travelling trajectory optimal during the delivery process. The objective of the proposed model is to minimize the travelling time and path length of the vehicle, which are the popular indicators in path optimization [9].…”

Section: Fig 2 Impact Of Commodity Market Conditions On Tariff Polimentioning

confidence: 99%

Assessment of the Impact of Globalization on the Development of the Russian Transport System

Podsorin

Ovsiannikova

2021

SHS Web of Conf.

View full text Add to dashboard Cite

Research background: The article describes the main trends in the globalization of economic processes, analyses the economic situation of world commodity markets, considers factors that influence the development of the transport system of Russia, defines the transport component in the cost of bulk cargo transported by Russian railways, presents a conceptual model of its formation for the purpose of improving tariff policy and competitiveness. A study of the dynamics of market conditions helps to identify factors that increase the efficiency of interaction between cargo-forming enterprises and organizations with the transport complex, develop and justify a system of measures to increase the efficiency of the transport system and ensure the sustainability of the national economy, as well as identify factors that contribute to globalization and the integration of production processes of transnational structures into the world economic system. Purpose of the article: To develop a methodological approach to assessing the impact of global commodity markets in the context of the globalization of economic processes on the development of the transport system of Russia. Methods: Analysis, classification, deduction, economic and mathematical modelling. Findings & Value added: The developed conceptual model for assessing the impact of global commodity markets in the context of the globalization of economic processes on the development of the country’s transport system contributes to the improvement of the tariff policy in the field of freight transportation, creates favourable conditions for increasing freight volumes for both transit and export-import cargoes.

show abstract

A Fissile Ripple Spreading Algorithm to Solve Time-Dependent Vehicle Routing Problem via Coevolutionary Path Optimization

Cited by 7 publications

References 39 publications

Study on the Shortest Reliable Path of Stochastic Time-Dependent Transportation Networks considering Waiting Time at Signalized Intersections

Study on the Shortest Reliable Path of Stochastic Time-Dependent Transportation Networks considering Waiting Time at Signalized Intersections

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

Assessment of the Impact of Globalization on the Development of the Russian Transport System

Contact Info

Product

Resources

About