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

Author(s):  
Ihda Septiyafi ◽  
Herry Suprajitno ◽  
Asri Bekti Pratiwi

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.

2013 ◽  
Vol 336-338 ◽  
pp. 2567-2571
Author(s):  
Li Hua Zhang ◽  
Ming Yang Wang

An open vehicle routing problem is studied. In this problem, multi-depot, heterogeneous-vehicle, fuel consumption and start-up costs of vehicles are considered, thus a genetic algorithm is given to solve this hard problem. In order to improve the performance of the genetic algorithm, a heuristic algorithm is provided to produce the initial population and participate in crossover. An example is given to illustrate the genetic algorithm.


2018 ◽  
Vol 27 (1) ◽  
pp. 394-417
Author(s):  
Jens Lysgaard ◽  
Ana Dolores López-Sánchez ◽  
Alfredo G. Hernández-Díaz

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