基于遗传算法的最优城市垃圾收运路线探究

Research on City Garbage Removal Routes Based on Genetic Algorithm

通过对垃圾收运路线的分析,可归结为组合规划问题。针对目前垃圾收运路线多采用TSP模型,建立了改进的遗传算法的垃圾收运优化模型,并运用计算机编程和搜索技术进行研究,并结合实例给出参数对运输路线进行计算机仿真。分别以垃圾收运车程最短和垃圾收运时间最少建立目标函数,并挖掘出约束条件,建立垃圾收运路线的数学模型。对传统的遗传算法进行改进,采用赌论策略选择个体进行遗传交叉操作,来求得目标函数的近似全局最优解。经实例仿真证明,建立的模型是合理的,表明赌论策略的遗传算法适合于复杂的垃圾收运路线的优化,运行收敛速度快,为优化路线提供了参考。

Through the analysis of garbage removal,we defined the issue as the combination planning.TSP model was currently used to find garbage removal routes.We established an optimization model based on improved Genetic Algorithm for Garbage Removal,then combined the model with computer programming and search techniques.We launched a study and carried out computer simulation combined with examples which gave parameters of transport routes.In this paper,we respectively established objective function aiming to the shortest path of Garbage Removal or the time it spent.Then dug out the constraints and established a mathematical model of garbage removal routes.We adopted the Gambling theory strategy to select the individual for genetic crossover,and then obtained the approximate global optimal solution of the objective function.The example simulation shows that the model we established is reasonable,and the Genetic Algorithm based on the Gambling theory strategy is proper for complicated optimization of garbage removal routes,furthermore its convergence is rapid.