首页> 外文期刊>Journal of Theoretical and Applied Information Technology >CAPACITATED MULTI DEPOT MULTI VEHICLE ROUTING PROBLEM USING GENETIC ALGORITHM (CASE STUDY: WATERING THE MEDAN CITY PARK)
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CAPACITATED MULTI DEPOT MULTI VEHICLE ROUTING PROBLEM USING GENETIC ALGORITHM (CASE STUDY: WATERING THE MEDAN CITY PARK)

机译:遗传算法电容多车库多车辆路由问题(案例研究:浇水棉兰市公园)

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Watering a city park is one of the steps taken to treat city parks in the city of Medan so that plants remain alive and fresh so they can reduce air pollution. The water capacity needed to water the plants in each location is adjusted to the area of the site to be watered. Therefore, the city park watering vehicle must be able to adjust the route to be passed with the capacity of water that can be carried. To determine the route that must be traversed in quite complex problems like this, Genetic Algorithms can be used to obtain an approach solution to the optimization problem in this case. The genetic algorithm will generate chromosomes that represent the route to be followed, then the chromosomes will go through the process of evaluation, selection, crossover, and mutation so that new chromosomes are produced by many generations. After several trials in the case of the Capacitated Vehicle Routing Problem using the Genetic Algorithm for determining the park watering route in Medan, the route was found to be the closest to optimal for depot A in the 173rd generation with a fitness value of 0.00292227 and the route for depot B at 148th generation with a fitness value of 0.00261028. From several trials, it can be concluded that the chance of finding the best route is influenced by the size of the population and the maximum number of generations used. The greater the population size and the maximum number of generations used, the more optimal the best route found.
机译:浇水城市公园是在棉兰市处理城市公园的步骤之一,以便植物保持活力,新鲜,因此可以减少空气污染。将植物在每个位置浇水所需的水容量被调节到待浇水的部位区域。因此,城市公园浇水车辆必须能够调整途径,以便通过可携带的水的容量传递。为了确定必须在这样的相同问题中遍历的路由,遗传算法可用于在这种情况下获得对优化问题的方法。遗传算法将产生代表要遵循的路线的染色体,然后染色体将通过评估,选择,交叉和突变的过程,以便通过许多代来产生新的染色体。经过几次试验在电容车辆路由问题使用遗传算法中使用遗传算法在棉兰确定公园浇水路线时,该路线被发现是第17 3R发电中的储物A最近的最佳途径,适合值为0.00292227和在第148代第148代的储存途径,适应值为0.00261028。从几次试验中,可以得出结论,找到最佳路线的机会受到人口大小的影响和所使用的最大几代人数。人口大小和所使用的最大几代人数越大,找到的最佳路线就越最佳。

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