Mathematical model based on genetic algorithms to optimize profits in an underground passenger transport company

Jorge Luis Mantilla Flores
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Abstract

The main objective of this research was to improve profits in an interprovincial passenger transport company, having designed a mathematical programming model and a genetic algorithm model with the purpose of reaching solutions for a future optimization of the company's profits. The type of research was applied, the technique that was applied was the survey and the sample was made up of all the variables of income, costs and profits of an interprovincial passenger transport company in the Peruvian territory. The results confirmed that the implementation of a mathematical model based on genetic algorithms contributes significantly to the optimization of profits, since the profit associated with the economic bus was improved, to the sleeper bus, to the mixed bus and to the super sleeper bus, achieving an optimal occupancy rate of 58.33%, 85.00%, 58.33% and 95.00%, respectively. The implemented model was based on a chromosome size of 19 bits, the population size was 10 chromosomes, the selection method is probabilistic with 4 chromosomes, crossing with four chromosomes, type of multipoint crossing and mutation process a from the second iteration of probabilistic type.
基于遗传算法的地下客运公司利润优化数学模型
本研究的主要目标是提高跨省客运公司的利润,设计了数学规划模型和遗传算法模型,以达到公司未来利润优化的解决方案。所采用的研究类型和所采用的技术是调查,样本由秘鲁境内一家省际客运公司的收入、成本和利润的所有变量组成。结果表明,基于遗传算法的数学模型的实施对利润优化有显著的促进作用,经济客车、卧铺客车、混合客车和超级卧铺客车的利润均得到了提高,最优入住率分别为58.33%、85.00%、58.33%和95.00%。所实现的模型以染色体长度为19位为基础,种群大小为10条染色体,选择方法为4条染色体的概率型、4条染色体的杂交型、多点杂交型和从概率型的第二次迭代开始的突变过程a。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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