Optimizing the Implementation of the Greedy Algorithm to Achieve Efficiency in Garbage Transportation Routes

Hanif Hidayatulloh; Pungkas Subarkah; Riky Dimas Dermawan; M. Abdul Rohman

doi:10.31764/jtam.v7i4.16612

Optimizing the Implementation of the Greedy Algorithm to Achieve Efficiency in Garbage Transportation Routes

Hanif Hidayatulloh, Pungkas Subarkah, Riky Dimas Dermawan, M. Abdul Rohman

Abstract

Until now, the waste problem is still a crucial problem, including in the Banyumas Regency area. The uncontrolled accumulation of garbage at the TPS will of course greatly disturb the comfort of the community around the TPS. As is the case with the accumulation of garbage at TPS (Garbage Disposal Sites) in North Purwokerto District. When searching for this garbage transportation route, the Greedy Algorithm works by finding the smallest weight point by calculating the route passed and calculating the weight depending on the weight of the stages that have been passed and the weight at the stage itself. Based on the results of the system testing that has been made, the shortest route for transporting waste from the starting point of the Banyumas Environment Office is to go to the final disposal site in Tipar, and return to the starting point of the Banyumas Environmental Office. So that the total distance traveled to return to the starting point is 53 km long. Based on the findings and discussions of this research, the results obtained are the determination of the shortest route from node A back to node A. Specifically, the route involves traveling from the DLH Banyumas Regency to TPS Grendeng, TPS Karangwangkal, TPS Pabuwaran, TPS Sumampir, TPS Purwanegara, TPS Bobosan, to TPA Tipar, and then returning to DLH Banyumas Regency. These results have implementable implications in the context of waste management in this area, with a total distance traveled of 53 kilometers.

Keywords

Greedy algorithm; Shortest route; Pathmapping; Waste disposal.

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References

Abu-Aisheh, Z., Raveaux, R., Ramel, J. Y., & Martineau, P. (2015). An exact graph edit distance algorithm for solving pattern recognition problems. ICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings, 1, 271–278. https://doi.org/10.5220/0005209202710278

Algabli, S., & Serratosa, F. (2018). Embedding the node-to-node mappings to learn the Graph edit distance parameters. Pattern Recognition Letters, 112, 353–360. https://doi.org/10.1016/j.patrec.2018.08.026

Calla, S., Guinchard, C., Moine, A., Novello-Paglianti, N., Nuninger, L., & Ogorzelec-Guinchard, L. (2023). Confronting the Uncertainties Associated with Long-Time Scales: Analysis of the Modes of Preservation of Memory of Radioactive Waste Burial Sites. Worldwide Waste, 6(1), 1–12. https://doi.org/10.5334/wwwj.75

Cerrone, C., Cerulli, R., & Golden, B. (2017). Carousel greedy: A generalized greedy algorithm with applications in optimization. Computers and Operations Research, 85(April), 97–112. https://doi.org/10.1016/j.cor.2017.03.016

Chen, L., Zhang, G., & Zhou, H. (2018). Fast greedy map inference for determinantal point process to improve recommendation diversity. Advances in Neural Information Processing Systems, 2018-Decem(NeurIPS), 5622–5633. https://doi.org/10.1007/s00521-019-04119-7

Das, R., Sahoo, L., Samanta, S., Simic, V., & Senapati, T. (2022). Identifying the Shortest Path of a Semidirected Graph and Its Application. Mathematics, 10(24), 1–13. https://doi.org/10.3390/math10244807

DeVore, R., Petrova, G., & Wojtaszczyk, P. (2013). Greedy Algorithms for Reduced Bases in Banach Spaces. Constructive Approximation, 37(3), 455–466. https://doi.org/10.1007/s00365-013-9186-2

Duchon, F., Babinec, A., Kajan, M., Beno, P., Florek, M., Fico, T., & Jurišica, L. (2014). Path planning with modified A star algorithm for a mobile robot. Procedia Engineering, 96, 59–69. https://doi.org/10.1016/j.proeng.2014.12.098

Giryes, R., Nam, S., Elad, M., Gribonval, R., & Davies, M. E. (2014). Greedy-like algorithms for the cosparse analysis model. Linear Algebra and Its Applications, 441, 22–60. https://doi.org/10.1016/j.laa.2013.03.004

Haasdonk, B. (2013). Convergence rates of the pod—greedy method. Mathematical Modelling and Numerical Analysis, 47(3), 859–873. https://doi.org/10.1051/m2an/2012045

Hussain, M., Chew, L. L., & Amirrudin, F. A. (2023). 6 *, 1,6. 15(3), 147–154.

Li, J., Zeng, X., Chen, M., Ogunseitan, O. A., & Stevels, A. (2015). “control-Alt-Delete”: Rebooting Solutions for the E-Waste Problem. Environmental Science and Technology, 49(12), 7095–7108. https://doi.org/10.1021/acs.est.5b00449

Malkov, Y., Ponomarenko, A., Logvinov, A., & Krylov, V. (2014). Approximate nearest neighbor algorithm based on navigable small world graphs. Information Systems, 45(January), 61–68. https://doi.org/10.1016/j.is.2013.10.006

Mokhirev, A., Gerasimova, M., & Pozdnyakova, M. (2019). Finding the optimal route of wood transportation. IOP Conference Series: Earth and Environmental Science, 226(1). https://doi.org/10.1088/1755-1315/226/1/012053

Porta, J., Parapar, J., Doallo, R., Barbosa, V., Santé, I., Crecente, R., & Díaz, C. (2013). A population-based iterated greedy algorithm for the delimitation and zoning of rural settlements. Computers, Environment and Urban Systems, 39, 12–26. https://doi.org/10.1016/j.compenvurbsys.2013.01.006

Puja Kekal, H., Gata, W., Nurdiani, S., Setio Rini, A. J., & Sely Wita, D. (2021). Analisa Pencarian Rute Tercepat Menuju Tempat Wisata Pulau Kumala Kota Tenggarong Menggunakan Algoritma Greedy. Jurnal Ilmiah Ilmu Komputer, 7(1), 9–15. https://doi.org/10.35329/jiik.v7i1.179

Quercia, D., Schifanella, R., & Aiello, L. M. (2014). The shortest path to happiness: Recommending beautiful, quiet, and happy routes in the city. HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media, 116–125. https://doi.org/10.1145/2631775.2631799

Ruslinda, Y., Aziz, R., & Putri, F. F. (2020). Analysis of Household Solid Waste Generation and Composition During The Covid-19 Pandemic In Padang City, Indonesia. Indonesian Journal of Environmental Management and Sustainability, 4(4), 116–124. https://doi.org/10.26554/ijems.2020.4.4.116-124

Sakharov, V., Chernyi, S., Saburov, S., & Chertkov, A. (2021). ScienceDirect ScienceDirect Automatization Search for the Shortest Routes in the Transport Automatization Search the Shortest Routes in the Transport Network Using for the Algorithm Network Using the Floyd-warshell Algorithm TransSiberia 2020 Conference. Transportation Research Procedia, 54(2020), 1–11. https://doi.org/10.1016/j.trpro.2021.02.041

Santi, M. N. (2019). Optimasi Biaya Jalur Tercepat Indarung-Unitas Menggunakan Algoritma Greedy. Menara Ilmu, XIII(11), 60–69. https://doi.org/10.31869/mi.v13i11.1647

Ubaidillah, M. A., & Gede Dwidasmara, I. B. (2020). Tourism Recommendation System in Bali Using Topsis and Greedy Algorithm Methods. JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), 8(3), 277. https://doi.org/10.24843/jlk.2020.v08.i03.p09

Wilt, C., & Ruml, W. (2014). Speedy versus greedy search. Proceedings of the 7th Annual Symposium on Combinatorial Search, SoCS 2014, 2014-Janua(SoCS), 184–192. https://doi.org/10.1609/socs.v5i1.18320

Xiang, D., Lin, H., Ouyang, J., & Huang, D. (2022). Combined improved A * and greedy algorithm for path planning of multi ‑ objective mobile robot. Scientific Reports, 1–12. https://doi.org/10.1038/s41598-022-17684-0

DOI: https://doi.org/10.31764/jtam.v7i4.16612