Penerapan Algoritma Kunang-Kunang pada Open Vehicle Routing Problem (OVRP)

Ihda Septiyafi, Herry Suprajitno, Asri Bekti Pratiwi
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Abstract

This paper aims to solve Open Vehicle Routing Problem using Firefly Algorithm. Open Vehicle Routing Problem (OVRP) is a variant of Vehicle Routing Problem (VRP)  where vehicles used to serve customers do not return to the depot after serving the last customer on each route. The steps of the Firefly Algorithm to handle OVRP are data input and initialization parameters, generating the initial population for each firefly, sorting population sources, calculating the value of the objective function and light intensity, comparing the intensity of light, performing movement, setting the best fireflies as g-best, doing random movement in the best fireflies as long as the maximum number of iterations has not been met. The program used to complete OVRP using the Firefly Algorithm is Borland C ++ and implemented in 3 case examples, namely small data with 18 customers, moderate data with 50 customers, and large data with 100 customers with the best total mileage of 211, 344 , 970.62, and 2531.83. The results obtained from the program output indicate that the more the number of iterations and the number of fireflies, then the results of the objective function (total mileage) obtained tend to be better so that these parameters affect the value of the objective function. While the absorption coefficient value (g) does not give effect to the value of the objective function.
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本文旨在利用萤火虫算法解决开放式车辆路径问题。开放式车辆路线问题(OVRP)是车辆路线问题(VRP)的一种变体,即用于服务客户的车辆在每条路线上为最后一个客户服务后不返回仓库。萤火虫算法处理OVRP的步骤是:数据输入和初始化参数,生成每只萤火虫的初始种群,对种群源进行排序,计算目标函数的值和光强,比较光强,进行移动,将最优萤火虫设置为g-best,在不满足最大迭代次数的情况下,对最优萤火虫进行随机移动。使用萤火虫算法完成OVRP的程序是Borland c++,分3个案例实现,分别是小数据18个客户,中等数据50个客户,大数据100个客户,最佳总里程分别为211、344、970.62、2531.83。从程序输出得到的结果表明,迭代次数和萤火虫数量越多,则得到的目标函数(总里程)的结果越好,因此这些参数会影响目标函数的值。而吸收系数值(g)对目标函数值没有影响。
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