scholarly journals Time-Dependent Vehicle Routing of Free Pickup and Delivery Service in Flight Ticket Sales Companies Based on Carbon Emissions

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Jingmei Guo ◽  
Chao Liu
Keyword(s):  
Traffic Congestion ◽  
Time Window ◽  
Set Partitioning ◽  
Time Dependent ◽  
Time Constraints ◽  
Pickup And Delivery ◽  
Routing Problem ◽  
Ticket Sales ◽  
Computational Performance ◽  
The Impact

The time-dependent pollution-routing problem of free pickup and delivery of passengers to the airport service (TDFPDS) is an extension of the time-dependent pollution-routing problems, arising in flight ticket sales companies for the service of free pickup and delivery of airline passengers to the airport. The problem consists of routing a fleet of vehicles in order to deliver a set of customers to the airport considering the traffic congestion, time window constraints, and maximum ride time constraints. The cost function includes fuel consumption and driver costs. We provide an analytical characterization of the optimal solutions for a fixed route and propose a novel heuristic for a given route based on the analysis of the illustrative examples. The heuristic algorithm is embedded into a set-partitioning model to produce high-quality routing plans. Finally, using wide variety of random instances, we present results on the computational performance of the heuristic and also on the impact of the congestion and the maximum ride time constraints.

Routing Electric Vehicles on Congested Street Networks

2020 ◽  
Author(s):  
Alexandre M. Florio ◽  
Nabil Absi ◽  
Dominique Feillet
Keyword(s):  
Electric Vehicles ◽  
Traffic Congestion ◽  
Control Policy ◽  
Time Dependent ◽  
Travel Times ◽  
Routing Problem ◽  
Promising Alternative ◽  
Street Networks ◽  
Time Control ◽  
The Impact

Freight distribution with electric vehicles (EVs) is a promising alternative to reduce the carbon footprint associated with city logistics. Algorithms for planning routes for EVs should take into account their relatively short driving range and the effects of traffic congestion on the battery consumption. This paper proposes new methodology and illustrates how it can be applied to solve an electric vehicle routing problem with stochastic and time-dependent travel times where battery recharging along routes is not allowed. First, a new method for generating network-consistent (correlated in time and space) and time-dependent speed scenarios is introduced. Second, a new technique for applying branch and price on instances defined on real street networks is developed. Computational experiments demonstrate the effectiveness of the approach for finding optimal or near-optimal solutions in instances with up to 133 customers and almost 1,500 road links. With a high probability, the routes in the obtained solutions can be performed by EVs without requiring intermediate recharging stops. An execution time control policy to further reduce the chances of stranded EVs is also presented. In addition, we measure the cost of independence, which is the impact on solution feasibility when travel times are assumed statistically independent. Last, we give directions on how to extend the proposed framework to handle recourse actions.

scholarly journals ABM-GIS simulation for urban freight distribution of perishable food

2018 ◽  
Vol 200 ◽  
pp. 00006 ◽  
Author(s):  
Hanane El Raoui ◽  
Mustapha Oudani ◽  
Ahmed El Hilali Alaoui
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Scheduling Algorithm ◽  
Time Windows ◽  
Freight Transport ◽  
Time Dependent ◽  
Traffic Condition ◽  
Routing Problem ◽  
Urban Freight ◽  
The Impact

Freight transport is essential to modern urban civilization. No urban area could exist without a powerful freight transport system. However, the distribution of perishable foods in urban areas is seen as a source of problems, due to traffic congestion, time pressures, and environmental impact. In this paper, an Agent-Based Model integrated with Geographic Information Systems (ABM-GIS) is designed for a time-dependent vehicle routing problem with time windows. This simulation model consists of determining the quickest routes to transport fresh products, estimating Vehicle kilometer traveled VKT and vehicle hour traveled VHT where speeds and travel times depend on the time of the day. Based on a case study, analyses of changes on traffic condition were conducted to get an insight into the impact of these changes on cost, service quality represented by the respect of time windows, and carbon emissions. The results reveal that traffic jams and restrictive time windows lead to additional cost, cause delays, and increase co2 emission. As for a short-term planning, time-dependent scheduling algorithm was proposed and assessed while extending time windows. Results have proved the potential saving in cost, travel time, and carbon emission.

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

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Wen Xu ◽  
JiaJun Li
Keyword(s):  
Vehicle Routing ◽  
Shortest Path ◽  
Traffic Congestion ◽  
Path Optimization ◽  
Time Dependent ◽  
Optimization Approach ◽  
Routing Problem ◽  
Shortest Path Problems ◽  
Travelling Time ◽  
Logistics Delivery

The time-dependent vehicle routing problems have lately received great attention for logistics companies due to their crucial roles in reducing the time and economic costs, as well as fuel consumption and carbon emissions. However, the dynamic routing environment and traffic congestions have made it challenging to make the actual travelling trajectory optimal during the delivery process. To overcome this challenge, this study proposed an unconventional path optimization approach, fissile ripple spreading algorithm (FRSA), which is based on the advanced structure of coevolutionary path optimization (CEPO). 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. Some significant factors usually ignored in other research are considered in this study, such as congestion evolution, routing environment dynamics, signal control, and the complicated correlation between delivery sequence and the shortest path. The effectiveness of the proposed approach was demonstrated well in two sets of simulated experiments. The results prove that the proposed FRSA can scientifically find out the optimal delivery trajectory in a single run via global research, effectively avoid traffic congestion, and decrease the total delivery costs. This finding paves a new way to explore a promising methodology for addressing the delivery sequence and the shortest path problems at the same time. This study can provide theoretical support for the practical application in logistics delivery.

scholarly journals Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Shichao Sun ◽  
Zhengyu Duan ◽  
Dongyuan Yang
Keyword(s):  
Large Scale ◽  
Time Window ◽  
Transportation Networks ◽  
Optimal Path ◽  
Time Dependent ◽  
Travel Times ◽  
Urban Network ◽  
Routing Problem ◽  
On The Road ◽  
Stochastic Time

This paper addressed the vehicle routing problem (VRP) in large-scale urban transportation networks with stochastic time-dependent (STD) travel times. The subproblem which is how to find the optimal path connecting any pair of customer nodes in a STD network was solved through a robust approach without requiring the probability distributions of link travel times. Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP), and algorithms for such TD-VRPs can also be introduced to obtain the solution. Numerical experiments were conducted to address STD-VRPTW of practical sizes on a real world urban network, demonstrated here on the road network of Shenzhen, China. The stochastic time-dependent link travel times of the network were calibrated by historical floating car data. A route construction algorithm was applied to solve the STD problem in 4 delivery scenarios efficiently. The computational results showed that the proposed STD-VRPTW model can improve the level of customer service by satisfying the time-window constraint under any circumstances. The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.

scholarly journals The Impact of Congestion on the Costs of Public Transport in Starogard Gdański

2019 ◽  
Vol 84 ◽  
pp. 7-18
Author(s):  
Marek Gierszewski ◽  
Aleksandra Koźlak
Keyword(s):  
Fuel Consumption ◽  
Public Transport ◽  
Traffic Congestion ◽  
Negative Impact ◽  
Urban Transport ◽  
Ticket Sales ◽  
Transport Services ◽  
Opt Out ◽  
High Level ◽  
The Impact

Congestion in the urban transport network is common not only in large agglomerations, but also in medium-sized cities in all countries that are characterized by a high level of socio-economic development. Traffic congestion has negative impact on economic, social, and environment development. The costs of congestion are borne by all users of the transport system, both drivers, passengers, entities providing transport services, as well as enterprises using freight transport services. The purpose of the article is to discuss the results of the study on the impact of congestion on the costs of public transport in a medium-sized city. The research method consisted in the analysis of vehicle road cards, fuel consumption statements for buses belonging to the Municipal Transport Company in Starogard Gdański and the examination of real bus travel times and the scale of delays caused by congestion on individual lines. The analysis of the data shows that thecompany bears much higher costs of fuel consumption, and passengers are exposed to bus arrivals and departures inconsistently with the timetable, prompting them to opt out of public transport services. This results in lower revenues from ticket sales and deterioration of the company’s financial result.

Column Generation for Split Pickup and Delivery Vehicle Routing Problem for Crude Oil Transportation

2012 ◽  
Author(s):  
Tsukasa Izuno ◽  
Tatsushi Nishi ◽  
Sisi Yin
Keyword(s):  
Crude Oil ◽  
Vehicle Routing ◽  
Column Generation ◽  
Vehicle Routing Problem ◽  
Feasible Solution ◽  
Set Partitioning ◽  
Pickup And Delivery ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Oil Transportation

The pickup and delivery crude oil transportation scheduling problem is to find an optimal assignment of requests to a fleet of tankers, sequence of visiting places, and loading and unloading volume of demand simultaneously in order to minimize the total cost with the capacity of the tankers. The problem can be formulated as a split pickup and delivery vehicle routing problem. We apply a column generation algorithm to solve the problem efficiently. In order to obtain a feasible solution by column generation, we propose an effective algorithm to generate a feasible solution satisfying the set partitioning constraints. Computational results demonstrate the effectiveness of the proposed method.

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