Open AccessDesigning Model for Truck Assignment Problem in Beef Delivery Using DBSCAN Algorithm
Author(s) -
Paduloh Paduloh
Publication year - 2020
Publication title -
journal of engineering and scientific research
Language(s) - English
Resource type - Journals
ISSN - 2685-1695
DOI - 10.23960/jesr.v1i2.26
Subject(s) - truck , dbscan , computer science , cluster analysis , product (mathematics) , transport engineering , business , automotive engineering , engineering , mathematics , artificial intelligence , canopy clustering algorithm , correlation clustering , geometry
In beef route delivery, many logistics companies have problems in making delivery plans correctly. Most logistics companies have a limited number of trucks, but there are shipping schedules, locations and volumes of demand is not fixed, in addition to returning products with various reasons that must be collected. Therefore the purpose of this study is to assign trucks to fulfill all beef delivery activities at a minimum cost. One reason for research on truck assignments in beef delivery is the high cost of shipping because it uses cold chains. This study uses the DBSCAN method to obtain density values based on customer distance to the central warehouse and the number of delivery requests, the data used in this study is the data of product delivery to customers for 6 months. Clustering research results using DBSCAN show the maximum values for epsilon 0.7 and Minpoints 2 are 3 clusters with 6 noises. with these results divided of trucks based on clusters is 2 trucks for the area of Banten, 7 trucks for the area of Jakarta, Bogor, and Bekasi, 2 trucks for Malang, and Surabaya. And 1 truck for the Bali area and noise or non-permanent delivery. Keywords: Truck assignment, DBSCAN, algorithm, beef delivery.