Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions

Shen, Ling; Tao, Fengming; Shi, Yuhe; Qin, Ruiru

doi:10.3390/ijerph16162982

Cited by 43 publications

(39 citation statements)

References 33 publications

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“…This paper randomly selects 8 cases from the database including small-scale study (Pro1, Pro2, Pro3, Pro4), medium-scale study (Pro5, Pro6, Pro7) and large-scale study (Pro8), the detailed information is shown in Table 5. Parameters of vehicles are shown in Table 6 according to references [21,50,51] and parameters of the proposed algorithm are shown in Table 7 according to references [10,[52][53][54].…”

Section: Test Casesmentioning

confidence: 99%

Optimization of Vehicle Routing for Waste Collection and Transportation

Tao

Yang

2020

IJERPH

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For the sake of solving the optimization problem of urban waste collection and transportation in China, a priority considered green vehicle routing problem (PCGVRP) model in a waste management system is constructed in this paper, and specific algorithms are designed to solve the model. We pay particular concern to the possibility of immediate waste collection services for high-priority waste bins, e.g., those containing hospital or medical waste, because the harmful waste needs to be collected immediately. Otherwise, these may cause dangerous or negative effects. From the perspective of environmental protection, the proposed PCGVRP model considers both greenhouse gas (GHG) emission costs and conventional waste management costs. Waste filling level (WFL) is considered with the deployment of sensors on waste bins to realize dynamic routes instead of fixed routes, so that the economy and efficiency of waste collection and transportation can be improved. The optimal solution is obtained by a local search hybrid algorithm (LSHA), that is, the initial optimal solution is obtained by particle swarm optimization (PSO) and then a local search is performed on the initial optimal solution, which will be optimized by a simulated annealing (SA) algorithm by virtue of the global search capability. Several instances are selected from the database of capacitated vehicle routing problem (CVRP) so as to test and verify the effectiveness of the proposed LSHA algorithm. In addition, to obtain credible results and conclusions, a case using data about waste collection and transportation is employed to verify the PCGVRP model, and the effectiveness and practicability of the model was tested by setting a series of values of bins’ number with high priority and WFLs. The results show that (1) the proposed model can achieve a 42.3% reduction of negative effect compared with the traditional one; (2) a certain value of WFL between 60% and 80% can realize high efficiency of the waste collection and transportation; and (3) the best specific value of WFL is determined by the number of waste bins with high priority. Finally, some constructive propositions are put forward for the Environmental Protection Administration and waste management institutions based on these conclusions.

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Section: Test Casesmentioning

confidence: 99%

Optimization of Vehicle Routing for Waste Collection and Transportation

Tao

Yang

2020

IJERPH

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“…The carbon emissions of transportation are proportional to fuel consumption. This paper refers to the literature [42] to calculate the amount of carbon dioxide from fuel consumption. Therefore, the carbon emissions E co 2 and its costs C 3 of the CVRP model can be expressed as Equations (4) and (5).…”

Section: Parameters and Variablesmentioning

confidence: 99%

“…If a facility is assigned excessive collection trips, the given limit is decreased. Table 10 presents the upper limits for all 6 DFs, where U r represents the given limit for disposal facility r. According to the previous studies [10,11,42,48], the parameters related to the CVRP model are shown in Table 11. The penalty value p is set to half of the fixed costs per unit vehicle.…”

Section: Experimental Designmentioning

confidence: 99%

Optimization of a Capacitated Vehicle Routing Problem for Sustainable Municipal Solid Waste Collection Management Using the PSO-TS Algorithm

Qiao

Tao

et al. 2020

IJERPH

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Sustainable management of municipal solid waste (MSW) collection has been of increasing concern in terms of its economic, environmental, and social impacts in recent years. Current literature frequently studies economic and environmental dimensions, but rarely focuses on social aspects, let alone an analysis of the combination of the three abovementioned aspects. This paper considers the three benefits simultaneously, aiming at facilitating decision-making for a comprehensive solution to the capacitated vehicle routing problem in the MSW collection system, where the number and location of vehicles, depots, and disposal facilities are predetermined beforehand. Besides the traditional concerns of economic costs, this paper considers environmental issues correlated to the carbon emissions generated from burning fossil fuels, and evaluates social benefits by penalty costs which are derived from imbalanced trip assignments for disposal facilities. Then, the optimization model is proposed to minimize system costs composed of fixed costs of vehicles, fuel consumption costs, carbon emissions costs, and penalty costs. Two meta-heuristic algorithms, particle swarm optimization (PSO) and tabu search (TS), are adopted for a two-phase algorithm to obtain an efficient solution for the proposed model. A balanced solution is acquired and the results suggest a compromise between economic, environmental, and social benefits.

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“…It is obviously better than that of the standard colony algorithm (3840.55). In order to demonstrate the superiority of this method, intelligent algorithm (this work), Multiple Ant Colony Optimization Algorithm (MACOA) [65] and Non-dominated Sorting Genetic Algorithm (NSGA) [66] are selected in this paper to solve the problem respectively. We assumed the number of iterations as 100 times.…”

Section: Effectiveness Analysis Of Iacats Algorithmmentioning

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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Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions

Cited by 43 publications

References 33 publications

Optimization of Vehicle Routing for Waste Collection and Transportation

Optimization of Vehicle Routing for Waste Collection and Transportation

Optimization of a Capacitated Vehicle Routing Problem for Sustainable Municipal Solid Waste Collection Management Using the PSO-TS Algorithm

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

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