Jia Mao’s research while affiliated with Jilin University and other places

Background: Serious secondary disasters caused by extreme natural weather conditions occur frequently, making it essential to establish a scientific and efficient modern emergency management system to maximize life-saving efforts. Methods: This study focuses on the uncertain environment of urban road networks and employs fuzzy theory to construct a 0–1 integer programming model for emergency evacuation paths that minimizes the average expected travel time. Results: We enhanced the neighborhood search strategy of the traditional ACO_time by incorporating the 2-opt and 3-opt perturbation mechanisms from the SA algorithm. Additionally, we utilized improved ant-volume and ant-perimeter models, along with their combinations, in the pheromone-updating mechanism of the basic ACO. The heuristic principles of the A* algorithm were integrated, introducing the joint influence of path and time into the heuristic function of the ACO algorithm. Conclusions: The IACO3 algorithm was tested on the Sioux Falls network and the Berlin Heisenheimer Center network. The computation time of the improved IACO3 algorithm was reduced by up to 20% compared to the original IACO3 algorithm in relation to the SA algorithm, with only a 4–5% increase in computation time compared to the ACO_time algorithm, which translates to an increase of merely 4–5 s. This demonstrates the superior solution efficiency of the IACO3 algorithm.

This paper explores the straw fodderisation project supply chain in Siping City, Jilin Province, with the raw material supply chain of the straw fermentation feed project as the research object. The relationship between the cost of the straw feed engineering supply chain and the carbon emission target is demonstrated through examples. The buffer analysis, overlay analysis and other functions of ArcGIS system are used to study the research data of Siping City, Jilin Province. With the map of Siping City, alternative points for storage facilities are obtained. Based on the deterministic model, a two-stage stochastic planning model for a multi-period three-stage straw supply chain is established by considering the uncertainty of straw raw material supply and the risk of facility failure. The uncertainty model was solved by improving the standard Drosophila algorithm, and the results of the deterministic and stochastic models were compared and sensitivity analyses were performed to optimise the straw collection, storage and transportation as a whole. The results show that considering uncertainty is necessary for straw supply chain design, which can improve the system efficiency, reduce the total cost of the supply chain, improve the ability of the supply chain to cope with the risk of facility failure, and promote the sustainable development of straw forage.

New concepts such as low-carbon economy, low-carbon production, low-carbon living and even low-carbon cities have become popular topics in environmental protection. The disassembly line part of reverse logistics is accompanied by high carbon emission, which is contrary to the original intention of sustainable development. In this paper, we design a systematic low-carbon layout for the disassembly line of the logistics processing center to address the problem of high carbon emissions caused by the unreasonable layout of the disassembly line. Taking the disassembly line in the logistics center of Company H as the research object, the process of the disassembly line is analyzed, and the SLP analysis method is applied to analyze the material flow and the material flow intensity level of the disassembly line layout, and three different optimization schemes are derived. Flexsim software was used to model and run the three initial layout schemes of the disassembly line, and the data related to the waiting time operation of each scheme were obtained. Finally, carbon emission and other disassembly-line-related indicators were introduced and weights were set, and the results were subjected to weighted gray correlation analysis to arrive at the optimal disassembly line layout optimization scheme. This study will provide reference for other reverse logistics processing center layout studies.

In this paper, we take the four-way shuttle system as the research object and establish the mathematical model of scheduling optimization based on the minimum time for the in/out operation optimization and path optimization scheduling problems of the four-way shuttle system. An improved genetic algorithm is used to solve the task planning, and an improved A* algorithm is used to solve the path optimization within the shelf level. The conflicts generated by the parallel operation of the four-way shuttle system are classified, and the improved A* algorithm based on the time window method is constructed for path optimization through the dynamic graph theory method to seek safe conflict-free paths. Through simulation example analysis, it is verified that the improved A* algorithm proposed in this paper has obvious optimization effect on the model of this paper.

In the context of sustainable development, this paper rationalises the outbound process of a four-way shuttle system with a focus on their modelling, performance evaluation and configuration using a parallel operation strategy to reduce resource waste, thus achieving sustainable development. The parallelism of the hoist and shuttle is innovatively incorporated into the four-way shuttle system, so the modelling content is divided into parallel and serial types. In the parallel operation strategy model, a separation–aggregation queueing network model is constructed, and the open-loop queueing network is innovatively solved using the maximum entropy method. In the serial operation strategy model, a semi-open-loop queuing network is constructed and solved using the geometric matrix method. By varying different parameters, the accuracy of the model is verified by Arena simulation with an error range of 10% or less, and the error of the system performance index calculation is reduced by 20% compared with the existing methods. Setting up 18 different sizes of shuttle systems provided a better performance than a single serial-operation strategy through the addition of parallel strategies, with an average reduction of 12.6% in the system response time and a minimum reduction of 1.8%. The conclusions of this paper were verified on the basis of an arithmetic case analysis.

Straw burning can cause serious environmental pollution, whereas returning straw to the fields, as a green production method, can improve the rural environment and strengthen the sustainable development of agriculture. According to statistics, China produced 797 million tons of straw in 2020, but the current straw return technology still needs to be improved; the ability of farmers to choose the correct amount of straw to be returned to the field and their awareness of environmental protection still need to be strengthened. Straw is still openly burned in some areas, causing environmental pollution and the waste of resources, which are contrary to the concept of sustainable development in China. In this study, we estimated the amount of straw resources in Heilongjiang Province, a major grain-producing province in China, by quantifying the production of major crops between 2011 and 2020. We then identified and analyzed the current problems in terms of policy support and other aspects. We used an integrated AHP-fuzzy evaluation method to evaluate the comprehensive benefits of different straw return amounts, and we determined the amount of straw that should be returned to the soil to produce the best comprehensive benefits. We provide suggestions for the current main problems regarding the amount of crop straw to return to the soil in Heilongjiang Province, arguing that choosing a reasonable straw return amount will help farmers increase profit, reduce environmental pollution, and contribute to the sustainable development of the environment.

With the development of China’s express delivery industry, the number of express packaging has proliferated, leading to many problems such as environmental pollution and resource waste. In this paper, the process of reverse logistics network design for express packaging recycling is given as an example in the M region, and a four-level network containing primary recycling nodes, recycling centers, processing centers, and terminals is established. A candidate node selection model based on the K-means algorithm is constructed to cluster by distance from 535 courier outlets to select 15 candidate nodes of recycling centers and processing centers. A node selection model based on the NSGA-II algorithm is constructed to identify recycling centers and processing centers from 15 candidate nodes with minimizing total cost and carbon emission as the objective function, and a set of Pareto solution sets containing 43 solutions is obtained. According to the distribution of the solution set, the 43 solutions are classified into I, II, and III categories. The results indicate that the solutions corresponding to Class I and Class II solutions can be selected when the recycling system gives priority to cost, Class II and Class III solutions can be selected when the recycling system gives priority to environmental benefits, and Class III solutions can be selected when the society-wide recycling system has developed to a certain extent. In addition, this paper also randomly selects a sample solution from each of the three types of solution sets, conducts coding interpretation for site selection, vehicle selection, and treatment technology selection, and gives an example design scheme.