scholarly journals Distribution Route Optimization for Electric Vehicles in Urban Cold Chain Logistics for Fresh Products under Time-Varying Traffic Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Zhixue Zhao ◽  
Xiamiao Li ◽  
Xiancheng Zhou
Keyword(s):  
Electric Vehicles ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Route Optimization ◽  
Cold Chain ◽  
Logistic Distribution ◽  
Time Varying ◽  
Traffic Conditions ◽  
Distribution Process ◽  
Fresh Products

Electric vehicles (EVs) have been widely used in urban cold chain logistic distribution and transportation of fresh products. In this paper, an electric vehicle routing problem (EVRP) model under time-varying traffic conditions is designed for planning the itinerary for fresh products in the urban cold chain. The object of the EVRP model is to minimize the total cost of logistic distribution that includes economic cost and fresh value loss cost. To reflect the real situation, the EVRP model considers several influencing factors, including time-varying road network traffic, road type, client’s time-window requirement, freshness of fresh products, and en route queuing for charging. Furthermore, to address the EVRP, an improved adaptive ant colony algorithm is designed. Simulation test results show that the proposed method can allow EVs to effectively avoid traffic congestion during the distribution process, reduce the total distribution cost, and improve the performance of the cold chain logistic distribution process for fresh products.

Low-carbon VRP for cold chain logistics considering real-time traffic conditions in the road network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qinyang Bai ◽  
Xaioqin Yin ◽  
Ming K. Lim ◽  
Chenchen Dong
Keyword(s):  
Road Network ◽  
Cold Chain ◽  
Time Varying ◽  
Low Carbon ◽  
Content Type ◽  
Distribution Costs ◽  
The Road ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Distribution Cost

PurposeThis paper studies low-carbon vehicle routing problem (VRP) for cold chain logistics with the consideration of the complexity of the road network and the time-varying traffic conditions, and then a low-carbon cold chain logistics routing optimization model was proposed. The purpose of this paper is to minimize the carbon emission and distribution cost, which includes vehicle operation cost, product freshness cost, quality loss cost, penalty cost and transportation cost.Design/methodology/approachThis study proposed a mathematical optimization model, considering the distribution cost and carbon emission. The improved Nondominated Sorting Genetic Algorithm II algorithm was used to solve the model to obtain the Pareto frontal solution set.FindingsThe result of this study showed that this model can more accurately assess distribution costs and carbon emissions than those do not take real-time traffic conditions in the actual road network into account and provided guidance for cold chain logistics companies to choose a distribution strategy and for the government to develop a carbon tax.Research limitations/implicationsThere are some limitations in the proposed model. This study assumes that there are only one distribution and a single type of vehicle.Originality/valueExisting research on low-carbon VRP for cold chain logistics ignores the complexity of the road network and the time-varying traffic conditions, resulting in nonmeaningful planned distribution routes and furthermore low carbon cannot be discussed. This study takes the complexity of the road network and the time-varying traffic conditions into account, describing the distribution costs and carbon emissions accurately and providing the necessary prerequisites for achieving low carbon.

Route optimization cold chain logistic distribution using greedy search method

OPSEARCH ◽  
2020 ◽  
Vol 57 (4) ◽  
pp. 1115-1130 ◽  
Author(s):  
Xiong Qiang ◽  
Martinson Yeboah Appiah ◽  
Kwasi Boateng ◽  
Frederick VonWolff Appiah
Keyword(s):  
Search Method ◽  
Route Optimization ◽  
Cold Chain ◽  
Logistic Distribution ◽  
Greedy Search

Route Optimization of Aquatic Product Transportation Based on an Improved Ant Colony Algorithm

2020 ◽  
Vol 24 (4) ◽  
pp. 488-493
Author(s):  
Chenxiao Yu ◽  
Zuiyi Shen ◽  
Pengfei Li ◽  
◽  
◽  
...  
Keyword(s):  
Ant Colony Algorithm ◽  
Time Window ◽  
Route Planning ◽  
Ant Colony ◽  
Route Optimization ◽  
Routing Problem ◽  
Aquatic Products ◽  
Aquatic Product ◽  
To Receive ◽  
Improved Ant Colony Algorithm

In this paper, the time window in which aquatic products must be delivered and the uncertainty of road conditions that affect the time at which customers are able to receive the goods are added as constraints in the optimization model of the Vehicle Routing Problem. The use of pheromones in the original ant colony algorithm was improved, and the waiting factor was added into the state transition rules to limit the information range. The improved ant colony algorithm was used to simulate the model with the example of aquatic product transportation route planning in Zhoushan city. The results show that this algorithm can optimize the transportation and distribution routes of aquatic products more effectively.

scholarly journals Optimization of Urban Cold Chain Transport Routes under Time-Varying Network Conditions

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Shouchen Liu ◽  
Cheng Zhang
Keyword(s):  
Time Window ◽  
Cold Chain ◽  
Service Reliability ◽  
Time Varying ◽  
Road Transportation ◽  
Artificial Immune ◽  
Urban Road ◽  
Road Speed ◽  
Fuzzy Time Window ◽  
Vehicle Path

Given the time-efficient characteristics of urban cold chain transportation and the time-varying characteristics of urban road speed, customers encounter the problem of limited vehicle path optimization due to a fuzzy time window. An optimization model of urban cold chain transportation with the objective function as the minimum total cost is constructed under the premise of service reliability, and an artificial immune particle swarm optimization algorithm is designed to solve the model. For an empirical analysis of Xiamen’s cold chain transportation, a two-stage solution involving “static optimization and dynamic optimization” is used to verify the effectiveness of the model and the practical value of this research. Results show that the time-varying model can effectively reflect the situation of urban road transportation and satisfy the timeliness requirement of urban cold chain transportation.

scholarly journals An Efficient Hybrid Algorithm for Energy Expenditure Estimation for Electric Vehicles in Urban Service Enterprises

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 2004
Author(s):  
Mariusz Izdebski ◽  
Marianna Jacyna
Keyword(s):  
Energy Expenditure ◽  
Electric Vehicles ◽  
Hybrid Algorithm ◽  
Ant Colony Algorithm ◽  
Environmental Safety ◽  
Utility Company ◽  
Service Companies ◽  
Charging Time ◽  
Urban Service ◽  
High Emission

The article deals with the decision problems of estimating the energy expenditure of low-emission fleets in urban service companies due to environmental safety. One of the most important problems of today’s transport policy of many city authorities is the ecological safety of its inhabitants. The basic measures are aimed at banning high-emission vehicles from city centers and promoting the introduction of zero-emission vehicles, such as electric or hybrid cars. The authors proposed an original approach to the decision model, in which the energy expenditure from the use of electric vehicles was defined as a criterion function. The boundary conditions took into account limitations typical of an electric vehicle, e.g., maximum range or battery charging time. To solve the problem, the authors proposed an efficient hybrid algorithm based on ant colony algorithm and genetic algorithm. The verification was made for the example of a utility company serving a medium-sized city in the eastern part of Poland.

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

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