Open AccessK-Means Clustering and Genetic Algorithm to Solve Vehicle Routing Problem with Time Windows Problem
Author(s) -
Adyan Nur Alfiyatin,
Wayan Firdaus Mahmudy,
Yusuf Priyo Anggodo
Publication year - 2018
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v11.i2.pp462-468
Subject(s) - vehicle routing problem , genetic algorithm , selection (genetic algorithm) , cluster analysis , computer science , algorithm , chromosome , mathematical optimization , computation , span (engineering) , population based incremental learning , routing (electronic design automation) , mathematics , engineering , artificial intelligence , biology , computer network , biochemistry , civil engineering , gene
Distribution is an important aspect of industrial activity to serve customers on time with minimal operational cost. Therefore, it is necessary to design a quick and accurate distribution route. One of them can be design travel distribution route using the k-means method and genetic algorithms. This research will combine k-means method and genetic algorithm to solve VRPTW problem. K-means can do clustering properly and genetic algorithms can optimize the route. The proposed genetic algorithm employs initialize chromosome from the result of k-means and using replacement method of selection. Based on the comparison between genetic algorithm and hybrid k-means genetic algorithm proves that k-means genetic algorithm is a suitable combination method with relative low computation time, are the comparison between 2700 and 3900 seconds.