Optimization of waste transport routes in Pati Regency using ArcGIS

Abstract

Based on the Recapitulation Data of the 2017 Pati District Waste from the Sanitation and Gardening Sector of the DPUTR Pati Regency shows that the amount of waste in Pati Regency is 3,082 tons / day. Meanwhile, the amount of waste transport to sanitary landfill only reaches 320 tons/day. Based on data from the Sanitation Strategy in Pati Regency 2015, Pati Regency Government was able to generate waste transportation service in urban areas by 7.17% and rural areas by 0.87%. This issue not comparable to the area of 1.580,37 km2 with a population density of 785 people/km2. The purpose of this study is to find the optimal value of waste transportation from the existing TTS point and New TTS points to the sanitary landfill by considering the distance and travel time with ArcGIS to improve waste transportation services in Pati Regency. Data collection methods in this study are: first, primary survey with direct interviews with Public Works Agency and Environmental Agency in Pati Regency about waste transportation systems at the polling station point. Second, the secondary surveys related to waste transportation system data namely density points for waste generation, number of garbage trucks and other data related to waste transportation systems. The results show that ArcGIS can help Optimize Travel Time by 39,04% and Optimization of Mileage by 37,38% and the volume of waste transported to reach 2.19% from Temporary Trash Shelter to Landfill.

Quantifying odour impacts from aged organic waste to be considered as a priority constraint in route optimization for waste collection trucks

“…A 9% and 13% increase in travelled distance was required when collecting the maximum volume and producing least odour impacts were set as top priorities, respectively. Higher increase percentages in travelled distances, of up to 28.5%, have been previously reported (Rahman and Maryono, 2020) which is expected when maximum collection volume is the first optimization priority. When shortest distance was travelled, the trucks failed to collect 81 m 3 of waste and allowed 53 bins to emit odours; while when setting the priority to collect the maximum volume, all the waste was collected within 48 hours and only 12 bins were served ‘late’ and left to produce odours.…”

“…Another complication that stems from misrepresentation of the time factor is that optimum routes, based on time, distance or cost, might in fact allow fresh solid waste to spend more time in either some of the bins along the path of collection or within the truck itself. When using ArcGIS to compute an optimal route for collection vehicles moving between the actual bins, two transfer stations, and the terminal drop off point of the landfill, the route that provided the highest reduction in time and distance (75% and 75.1%, respectively) actually resulted in a 75% reduction in collected waste volumes; when compared to current collection routes (Rahman and Maryono, 2020). This obvious failure in design is due to poor scheduling of bin visits caused by an optimization algorithm that was strictly designed to program trucks to hit certain locations along their shortest path, regardless of the volume of waste in the bins, leading to collection of empty and half empty bins.…”

Estimating baseline CO2 emission from waste collection and transport activity to TPST Bantargebang, Jakarta

“…The ArcGIS was used to analyze proximity in buffering, overlay, and network analysis, which served as the optimum pathfinder using the transport time and length parameters [3,4]. Detailed spatial information was needed, such as geographical data, street data, TPS coordinates, and other spatial data related to waste transport from TPS to TPST Bantargebang.…”

“…This research complements findings on the CO2 emission calculation in TPST Bantargebang, particularly in the waste treatment process. The author noted that recent studies [1,3,4] discussed waste transportation models in other cities in Indonesia, but no studies had been conducted in Jakarta. This research urged to provide a baseline input for DKI Jakarta Governor Regulation No.…”

Analisis Rute Pengangkutan Sampah Domestik Kota Malang Berbasis Aplikasi Google Map

“…Hal tersebut sesuai dengan beberapa hasil penelitian terdahulu yaitu Pola transportasi sampah dari TPS ke tempat pembuangan sampah di berbagai kota di Indonesia seperti Medan, Pati, Bogor, dan Semarang melibatkan teknik optimasi untuk meminimalkan jarak dan biaya perjalanan. Studi di Medan dan Pati menggunakan algoritma seperti Clarke & Weight Saving, Floyd Warshall, dan ArcGIS untuk mengoptimalkan rute transportasi limbah, menghasilkan pengurangan jarak tempuh yang signifikan (Syahputri et al, 2020) (Rahman & Maryono, 2020).…”