Multi-Depot Open Vehicle Routing Problem with Time Windows Based on Carbon Trading

Shen, Ling; Tao, Fengming; Wang, Songyi

doi:10.3390/ijerph15092025

Cited by 69 publications

(56 citation statements)

References 42 publications

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“…Both carbon trade price and carbon quota in carbon trading mechanism affect total costs and carbon emissions in VRP model [31]. However, in this work, additionally considering customer satisfaction is also possible to affect the final environmental influences.…”

Section: Influences Of Carbon Trading and Customer Satisfaction Consimentioning

confidence: 97%

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Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window

Wang

Wen

2020

Sustainability

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Due to the rise of social and environmental concerns on global climate change, developing the low-carbon economy is a necessary strategic step to respond to greenhouse effect and incorporate sustainability. As such, there is a new trend for the cold chain industry to establish the low-carbon vehicle routing optimization model which takes costs and carbon emissions as the measurements of performance. This paper studies a low-carbon vehicle routing problem (LC-VRP) derived from a real cold chain logistics network with several practical constraints, which also takes customer satisfaction into account. A low-carbon two-echelon heterogeneous-fleet vehicle routing problem (LC-2EHVRP) model for cold chain third-party logistics servers (3PL) with mixed time window under a carbon trading policy is constructed in this paper and aims at minimizing costs, carbon emissions and maximizing total customer satisfaction simultaneously. To find the optimal solution of such a nondeterministic polynomial (NP) hard problem, we proposed an adaptive genetic algorithm (AGA) approach validated by a numerical benchmark test. Furthermore, a real cold chain case study is presented to demonstrate the influence of the mixed time window’s changing which affect customers’ final satisfaction and the carbon trading settings on LC-2EHVRP model. Experiment of LC-2EHVRP model without customer satisfaction consideration is also designed as a control group. Results show that customer satisfaction is a critical influencer for companies to plan multi-echelon vehicle routing strategy, and current modest carbon price and trading quota settings in China have only a minimal effect on emissions’ control. Several managerial suggestions are given to cold chain logistics enterprises, governments, and even consumers to help improve the development of cold chain logistics.

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Section: Influences Of Carbon Trading and Customer Satisfaction Consimentioning

confidence: 97%

“…Shen el al. introduced a carbon trading mechanism in multiple depots of VRP with time window to achieve carbon reduction goals [31]. Qin et al also introduced a carbon trading mechanism to calculate carbon emissions' costs in cold chain logistics [32].…”

Section: Vehicle Routing Problem With Environmental Concernsmentioning

confidence: 99%

Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window

Wang

Wen

2020

Sustainability

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“…Then, Wang et al [29] employed an adaptive genetic algorithm combined with greedy algorithm to investigate the impact of carbon tax on carbon emissions in an inventory routing problem. Shen et al [30] explored the adaptive genetic algorithm, which can dynamically adjust the crossover and mutation probability, to survey the impact of the carbon trading mechanism on carbon emissions in multi-depot open VRP. Niu et al [31] proposed a green open VRP with time windows by minimizing the comprehensive routing cost, including the fuel cost, carbon emissions cost and driver cost.…”

Section: Research Considering Carbon Emissionsmentioning

confidence: 99%

Optimization of Transportation Routing Problem for Fresh Food by Improved Ant Colony Algorithm Based on Tabu Search

et al. 2019

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With the continuous improvement of people's living standards and their increasing demand for fresh food, the cold chain logistics industry has developed rapidly. One of the biggest challenges to today's cold chain logistics is to offer fresh food while minimizing CO 2 emissions. The fresh degree and CO 2 emissions are involved in the vehicle routing optimization problem in the cold chain logistics. In order to meet the quality requirement for fresh agricultural products and low carbon logistics, a novel routing optimization model considering the costs of quality deterioration and carbon emissions (Low Carbon and Freshness Degrees Vehicle Routing Problem (LCFD-VRP)) for cold chain distribution was established in this study. This model takes into account the fixed cost, fuel cost and time window penalty cost. An improved ant colony algorithm (IACA) is used to optimize the whole vehicle distribution routing with its strong global search ability. Tabu Search (TS) algorithm is used to search the single vehicle distribution routing with its good local search ability. An IACA combined with TS (IACATS) was proposed to solve the above LCFD-VRP model. The practicability of the model and the effectiveness of the above improved algorithm are verified using a real case study. The results of Zhoushan Dayang Refrigerated Logistics Co., Ltd. showed that, compared with the traditional algorithm, IACATS could reduce the dispatching of two refrigerated vehicles, thus lowering the total cost by 4.94%, shortening the actual transportation distance by 5.50% and cutting the total CO 2 emissions by 8.9%. Therefore, the LCFD-VRP model can effectively help to achieve the low carbon emissions, multi-variety and low-cost distribution of fresh agricultural products. The proposed model and IACATS algorithm would be used to optimize VRP in cold chain enterprises. The results of this study also provide management suggestions for cold chain enterprises to effectively balance economic cost and environmental cost.Sustainability 2019, 11, 6584 2 of 22 has higher requirements for quality and timeliness [2]. The normal operation of refrigeration equipment produces a large amount of CO 2 emissions and other greenhouse gases generated from distribution vehicles in the process of delivery. It leads to an increase in greenhouse gases and, as a result, air pollution and greenhouse effect will be intensified. The increased carbon emissions not only pollute the environment, but also raise the cost of logistics enterprises due to the implementation of national carbon-taxing policies [3]. Therefore, how to reduce carbon emissions in cold chain logistics, thereby alleviating the global warming caused by the greenhouse effect, has become a popular issue in the research field of cold chain logistics distribution routes [4].In recent years, the optimization of cold chain logistics distribution routes has attracted extensive academic attention [5,6]. Although the above-mentioned studies have considered the impacts of various cost factors on cold chain logistics, t...

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“…A variety of factors such as three-dimensional customer locations, gravity, vehicle speed, vehicle operating time, vehicle capacity, rolling resistance, air density, road grade, and inertia were considered to estimate greenhouse gas emissions. Recently, Shen et al [38] proposed a TDVRP that considers the driver's salary and penalty costs in addition to fuel costs and carbon emission trading costs. Shen et al [38] named it a low-carbon multi-depot open vehicle routing problem with time windows (MDOVRPTW).…”

Section: Routing With Uavsmentioning

confidence: 99%

“…Recently, Shen et al [38] proposed a TDVRP that considers the driver's salary and penalty costs in addition to fuel costs and carbon emission trading costs. Shen et al [38] named it a low-carbon multi-depot open vehicle routing problem with time windows (MDOVRPTW). Open VRP has two kinds of vehicles, as follows: Company-owned and rental.…”

Section: Routing With Uavsmentioning

confidence: 99%

Mathematical Investigation on the Sustainability of UAV Logistics

et al. 2019

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Unmanned aerial vehicles (UAVs) are expected to make groundbreaking changes in the logistics industry. Leading logistics companies have been developing and testing their usage of UAVs recently as an environmentally friendly and cost-effective option. In this paper, we investigate how much the UAV delivery service is environmentally friendly compared to the traditional ground vehicle (GV) delivery service. Since there are fuel (battery) and loadable weight restrictions in the UAV delivery, multi-hopping of UAV is necessary, which may cause a large consumption of electrical energy. We present a two-phase approach. In Phase I, a new vehicle routing model to obtain optimal delivery schedules for both UAV-alone and GV-alone delivery systems is proposed, which considers each system's restrictions, such as the max loadable weight and fuel replenishment. In Phase II, CO 2 emissions are computed as a sustainability measure based on the travelling distance of the optimal route obtained from Phase I, along with various GV travel-speeds. A case study finds that the UAV-alone delivery system is much more CO 2 efficient in all ranges of the GV speeds investigated.

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Multi-Depot Open Vehicle Routing Problem with Time Windows Based on Carbon Trading

Cited by 69 publications

References 42 publications

Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window

Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window

Optimization of Transportation Routing Problem for Fresh Food by Improved Ant Colony Algorithm Based on Tabu Search

Mathematical Investigation on the Sustainability of UAV Logistics

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