Changes in CO2 Emissions Induced by Agricultural Inputs in China over 1991–2014

Wang, Xiuhong

doi:10.3390/su8050414

Cited by 21 publications

(17 citation statements)

References 22 publications

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“…For example, supposing that the route gene sequence of the t-th individual in the population is [4,5,6,3,1,2] and the corresponding customer demand is [3,2,2,4,1,3], the vehicle gene sequence is [2,3,1,4,5], and the corresponding vehicle type is [1,2,2,3,3], and the corresponding maximum load of the vehicle type is [3,5,5,4,4]. According to the above task assignment, it is known that the assigned task is:…”

Section: Fitness Calculationmentioning

confidence: 99%

“…In recent years, global warming is an issue that cannot be ignored, and China's carbon emissions have also received widespread attention [1]. Moreover, at the United Nations Climate Conference in Copenhagen, China promised to reduce carbon emissions per unit of GDP to 50-60% of the 2005 level by 2020; however, the carbon emissions in China are at a high level, and most of it comes from fossil fuel consumption [2].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm

Cao

Zuo

et al. 2020

Sustainability

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In order to reduce the distribution cost of fresh food logistics and achieve the goal of green distribution at the same time, the Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem (GFLHF-VRP) model is established. Based on the particularity of the model, an improved genetic algorithm called Genetic Algorithm with Adaptive Simulated Annealing Mutation (GAASAM) is proposed in which the mutation operation is upgraded to a simulated annealing mutation operation and its parameters are adjusted by the adaptive operation. The experimental results show that the proposed GAASAM can effectively solve the vehicle routing problem of the proposed model, achieve better performance than the genetic algorithm, and avoid falling into a local optimal trap. The distribution routes obtained by GAASAM are with lower total distribution cost, and achieve the goal of green distribution in which energy, fuel consumption and carbon emissions are reduced at the same time. On the other hand, the proposed GFLHF-VRP and GAASAM can provide a reliable distribution route plan for fresh food logistics enterprises with multiple types of distribution vehicles in real life, which can further reduce the distribution cost and achieve a greener and more environment-friendly distribution solution. The results of this study also provide a managerial method for fresh food logistics enterprises to effectively arrange the distribution work with more social responsibility.

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Section: Fitness Calculationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm

Cao

Zuo

et al. 2020

Sustainability

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“…In order to improve customer satisfaction, the freshness of products should be considered in the optimization of the cold chain logistics distribution route. Wang et al [25] proposed that the freshness of perishable products should be taken as a criterion when measuring the optimal distribution route, and that the multi-distribution center cold chain vehicle routing problem be studied with the objectives of minimum transportation cost, vehicle travel time and product perishability. Yi et al [26] introduced the freshness loss coefficient and established a multi-objective optimization model for the fresh agricultural products distribution route by considering customer satisfaction and the total cost.…”

Section: Research Considering Fresh Degreesmentioning

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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“…In recent years, the issue of greenhouse gas emissions reduction has become a popular topic in the world [1]. At the United Nations Climate Conference in Copenhagen, China promised to reduce carbon emissions per unit of GDP to 40-50% of the 2005 levels by 2020 [2].…”

Section: Introductionmentioning

confidence: 99%

Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)

2019

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Low-carbon production has become one of the top management objectives for every industry. In garment manufacturing, the material distribution process always generates high carbon emissions. In order to reduce carbon emissions and the number of operators to meet enterprises’ requirements to control the cost of production and protect the environment, the paths of material distribution were analyzed to find the optimal solution. In this paper, the model of material distribution to obtain minimum carbon emissions and vehicles (operators) was established to optimize the multi-target management in three different production lines (multi-line, U-shape two-line, and U-shape three-line), while the workstations were organized in three ways: in the order of processes, in the type of machines, and in the components of garment. The NSGA-II algorithm (non-dominated sorting genetic algorithm-II) was applied to obtain the results of this model. The feasibility of the model and algorithm was verified by the practice of men’s shirts manufacture. It could be found that material distribution of multi-line layout produced the least carbon emissions when the machines were arranged in the group of type.

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Changes in CO2 Emissions Induced by Agricultural Inputs in China over 1991–2014

Cited by 21 publications

References 22 publications

Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm

Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm

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

Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)

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