Determining time-dependent minimum cost paths under several objectives

Heni, Hamza; Coelho, Leandro C.; Renaud, Jacques

doi:10.1016/j.cor.2019.01.007

Cited by 14 publications

(7 citation statements)

References 42 publications

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“…Zhao et al [14] considered the effects of time-varying road network traffic volumes and road types. Constructing a model for the path optimization problem of electric vehicles, Heni et al [15] investigated the dynamic path of traffic and the instantaneous speed of traffic networks. Poonthalir et al [16] proposed a computational model for the effect of triangularly distributed variable speeds on fuel consumption.…”

Section: A Road Trafficmentioning

confidence: 99%

Low-Carbon Cold-Chain Logistics Path Optimization Problem Considering the Influence of Road Impedance

Zhang

2023

IEEE Access

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An improved road impedance function in conformity with Chinese city road traffic is designed for calculating the actual transportation time based on real-time traffic information and the complex road environment in the city. The objective function minimizes the total distribution cost, including fixed cost, transportation cost, damage cost, energy cost, penalty cost, and carbon emission cost. A mathematical model is constructed for cold-chain logistics distribution path optimization considering the influence of road impedance. The model is solved using three particle swarm optimization algorithms with improved weights. The experimental results show that the self-adaptive weighted particle swarm optimization algorithm is more efficient in solving this model. Experimental results obtained from the cold-chain logistics path optimization model considering road impedance compared to those of the model without road impedance indicate that the former are closer to the actual situation. Based on the changes in carbon emission and total cost under different carbon taxes, we analyze the critical carbon tax value and the optimal carbon tax value range to improve the economic and environmental benefits in the distribution process. This study should prove to be of great practical significance and application value for logistics enterprises to conduct rational planning of path problems.INDEX TERMS Real-time traffic, road impedance function, particle swarm optimization algorithm, coldchain logistics, critical carbon tax value.

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Section: A Road Trafficmentioning

confidence: 99%

Low-Carbon Cold-Chain Logistics Path Optimization Problem Considering the Influence of Road Impedance

Zhang

2023

IEEE Access

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“…However, it is known that the road gradient has one of the most significant influences on vehicle fuel consumption, as shown in Masmoudi et al (2018b). Heni et al (2019) developed the traditional CMEM by considering both fixed speeds or different speeds over time for each arc. Recently, Heni et al (2021) provided effective machine learning tools to estimate fuel consumption by considering more realistic conditions than traditional CMEM, such as the time-varying speed and traffic frequency.…”

Section: Measuring Fuel Consumption In Routing Problemsmentioning

confidence: 99%

Plug-in hybrid electric refuse vehicle routing problem for waste collection

Masmoudi

Coelho

Demir

2022

Transportation Research Part E: Logistics and Transportation Re

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“…In the continuous approach, unlike the discrete one, the travel time function is continuous, and speed over time is a discrete function. The most well-known model of this condition is from [4], which has been used in several studies [9][10][11][12][13][14][15]. In the stochastic approach, attempts are made to explain the stochastic nature of travel time using the Markov chain theory or stochastic variables [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A Novel Travel Time Estimation Model for Modeling a Green Time-Dependent Vehicle Routing Problem in Food Supply Chain

et al. 2022

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In a green time-dependent vehicle routing optimisation problem, if the travel time is not well estimated, the values of the objective function (emissions) for different solutions will be obtained with less accuracy, which leads to wrong decision making. The purpose of this paper is to propose an accurate travel-time estimation model. The model was developed by considering the different multiple traffic modes through a continuous approach. Moreover, in this model, it was assumed that the route between two nodes was a combination of different segments (i.e., expressway, boulevard, main street, auxiliary street, alley, etc.), and the speed level varied along the route and depended on the segments of the route. Congestion is a key factor affecting the delivery time of food to customers. To assess the reliability of the model, data from the delivery and sales network of the oldest and biggest beverage manufacturer in Iran was used. A new congestion pattern was identified based on the analysis of 272 routes and several rules were described that proved the above assumption about congestion. The travel time estimated for 30 random vehicles with random departure times were compared with data from Google Maps through statistical analyses.

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Determining time-dependent minimum cost paths under several objectives

Cited by 14 publications

References 42 publications

Low-Carbon Cold-Chain Logistics Path Optimization Problem Considering the Influence of Road Impedance

Low-Carbon Cold-Chain Logistics Path Optimization Problem Considering the Influence of Road Impedance

Plug-in hybrid electric refuse vehicle routing problem for waste collection

A Novel Travel Time Estimation Model for Modeling a Green Time-Dependent Vehicle Routing Problem in Food Supply Chain

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