Improved Genetic Algorithm for Solving Green Path Models of Concrete Trucks
Source abstract
Abstract
In this paper, for the problem of high total fuel consumption of distribution trucks when multiple concrete-mixing plants distribute concrete together, we established a green fuel consumption model for distribution trucks and solved the model with an improved genetic algorithm to obtain a green distribution scheme for trucks. Firstly, the fuel consumption model is established for the characteristics of commercial concrete tankers; secondly, the adaptive elite retention strategy, adaptive crossover, mutation operator, and immune operation are added to the genetic algorithm to improve it; and finally, the model is solved to obtain the green distribution scheme. The total fuel consumption in this experiment was 189.6 L when the green distribution scheme was used; compared to the total fuel consumption under the original scheme (240 L), the total fuel consumption was reduced by 21.25%. The experimental results show that the total fuel consumption of delivery trucks can be significantly reduced based on the established green fuel consumption model, and the improved genetic algorithm can effectively solve the model.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Vehicle Routing Optimization Methods · Advanced Manufacturing and Logistics Optimization · Smart Parking Systems Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Funding
the National Natural Science Foundation of China · Henan 2023 Research and development of key technologies
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