基于Dijkstra和遗传模拟退火算法的煤炭运输路径优化

Junqi Liang, X. He
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摘要

本文探讨了煤炭应急运输路线问题。考虑了影响煤炭运输的主要因素,包括运输时间、运输成本以及中转运输所需的额外时间和成本。考虑到水路运输时间过长等不利因素,煤炭的两种主要运输方式是公路运输和铁路运输。本文建立了煤炭应急运输路径优化模型。以时间和成本最小为目标函数,采用Dijkstra和遗传模拟退火混合算法求解煤炭运输路径模型。通过Dijkstra算法初步得到了一些路径较短的传输路径,并将这些路径作为遗传模拟退火算法的输入路径。在该混合算法的基础上,通过种群交叉和种群突变相结合,生成了最优的运输方式组合。混合算法可以较快地找到准确的传输方法。
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Optimization of Coal Transportation Path Based on Dijkstra and Genetic-Simulated Annealing Algorithm
This paper explores the issue of emergency transportation routes for coal. The main factors influencing the transportation of coal are taken into account, including transport time, transport costs, and the additional time and costs required for transit transport. The two primary modes of transport for coal are road transport and rail transport, considering unfavorable factors such as the excessive time consumed by waterway transport. In this paper, a coal emergency transport path optimization model is constructed. Moreover, this paper applies a hybrid algorithm of Dijkstra and genetic-simulated annealing to solve the coal transport path model, with minimum time and minimum cost as the objective function. A few transport routes with short paths are initially obtained by Dijkstra's algorithm, and these routes are used as input paths for the genetic-simulated annealing algorithm. Based on this hybrid algorithm, the optimal combination of transport modes is generated by combining population crossover and mutation. The hybrid algorithm can find the exact transport method relatively quickly.
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