Open AccessWaste Transportation Route Optimization in Malang using Network Analysis
Author(s) -
Ardiansyah Putra,
Aniendhita Rizki Amalia,
R. K. H. Putro,
L. F. Darmayani
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/506/1/012033
Subject(s) - truck , population , waste management , trips architecture , transport engineering , engineering , tonne , environmental science , demography , sociology , aerospace engineering
Malang has a projection population of 861,414 people in 2018. This big population would cause waste generation that is increasing every day. Waste generation was recorded at the amount of up to 646.07 tonnes/day just from Malang in 2018. However, waste transported to landfill was only 516.84 tonnes/day. It means that the load factor was only 84.73%. Waste transportation problems come from various factor. Malang had only 68 temporary waste storage (TPS) that were spread in the city. This number of TPS was not commensurate with waste generation that was generated every day. The limited number of trucks was another issue considering Malang only had 35 trucks capable of making three trips per day. Limited number of trucks and TPS has led to a bad situation for transporting waste. As a result, many wastes were left behind in TPS. Therefore, it is necessary to analyze the best route for the trucks sso that the waste route can be optimized using network analysis in ArcGIS. This study assessed one route of a truck which had the longest distance (TPS Tunggul Wulung) with a total of 60.2 km at a time that it reached in 113.8 minutes. The result of the network analysis method with ArcGIS showed that the total distance declined to 36.2 km. This indicates that the alternative route shown by the shortest distance method has been able to reduce the existing distance for waste transportation route by 24 km. This certainly resulted in the decline in travel time for ± 39 minutes/day. This indicates that the existing routes can be optimized by alternative route network analysis in ArcGIS.