Publication: Supportive decision model for designing optimal geo-spatial route in the municipal solid waste transportation
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Date
2020-07-01
Authors
Salleh, Abdul Hakim
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Abstract
Waste collection transport costs are one of the most important aspects of waste management in the world, as they cover most of the operating budgets. The certainty of traveling the shortest distance will lead to the least cost of the waste collection method is not a true assumption, as it does not represent the actual geographical situation and condition of the area, which will certainly affect the smooth travel of the waste compactor vehicle. This study therefore sought to optimize the waste transport strategy through a thorough investigation of road information in the study area of Alor Setar district in Kota Setar, Kedah. The information collected in the road category was, in particular, the design of the road that describes the physical nature of the road itself, the network of the road that explains the connectivity of the road and the human-related factors involved in the interaction or relationship between motor vehicles and pedestrians. A smooth traveling vehicle environment will result in less stress in the internal combustion and compartment of the vehicle, making it possible for the vehicle to operate at its optimum performance. Through ArcGIS Network Analysis, the road spatial data system was developed by recording selected categories of road information and analysing its efficiency to ensure the least impact on the movement of the vehicle during the waste bin collection process and returning to the disposal sites. The study applies the weighting criteria to determine the optimized route using the three-stage cost model development, i.e. priority node stage, primary weighting and secondary weighting. The best optimal route of the area has been developed with the least disturbances based on the twelve criteria set out for the road and the priorities set by the supportive decision makers. The priorities show the top three criteria with highest disturbances in the study area were the traffic lights (20%), junctions (19%), and on road parking (14%). The result shows the novel secondary weighting cost model has higher correlation coefficient with both the travel distance and time, compared to the primary weighting, in determining the disturbances of the route.