Authors : Chukwuogo Okwuchukwu; Ike Mgbeafulike

Volume/Issue : Volume 9 - 2024, Issue 10 - October

Google Scholar : https://tinyurl.com/bdddf3j4

Scribd : https://tinyurl.com/26asz4dd

DOI : https://doi.org/10.38124/ijisrt/IJISRT24OCT1746

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This study explores the application of Dijkstra's algorithm to enhance waste disposal management systems, focusing on optimizing routing for efficient waste disposal. By modeling waste disposal pathways, the research aims to identify the shortest and most cost-effective routes, thereby reducing both pollution and operational costs. The analysis demonstrates that Dijkstra's algorithm can effectively streamline waste collection processes in Abakaliki, Ebonyi State, Nigeria, enabling the waste management board to minimize distance, time, and expenses associated with waste transportation. The developed model is both scalable and adaptable, promoting the integration of Geographic Information Systems (GIS) and real-time data for dynamic route optimization. The findings suggest significant potential for this approach not only in waste management but also in other domains such as traffic management and urban planning. This paper advocates for further exploration of user-friendly interfaces and alert systems to enhance operational efficiency. This research highlights the overall transformative potential of Dijkstra's algorithm in improving the sustainability and effectiveness of municipal services.

Keywords : Waste Management, Waste Disposal, Waste Pollution, Geographic Information System (GIS), Geospatial, Technology, Information And Communication Technology (ICT) Application, Dijkstra’s Algorithm, Shortest Path And Machine Learning.

References :

1.  Akhtar M., Hannan M. A., Begum R. A., Basri H., & Scavino E. (2017) Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization. Waste Manag., vol. 61, pp. 117–128.
2. Amuda, O. S., Adebisi, S. A., Jimoda, L. A., & Alade, A. O. (2014). Challenges and Possible Panacea to the Municipal Solid Wastes Management in Nigeria. Journal of Sustainable Development Studies, 6.
3. Chukwuogo, O. E., & Mgbeafulike, I. J. (2024). Placing aside a strategy that makes use of Dijkstra's algorithm to determine the most cost-effective and efficient route for managing trash properly while reducing pollution. International journal of progressive research in science and engineering, 5(6), 38-41
4. Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerical Mathematics. vol. 1, no. 1, pp. 269–271.
5. Gazder U. (2018). Framework for Route Optimization of Solid Waste Collection. IET Conf. Proc., pp. 39–44.
6. Gilardino, A., Rojas J., Mattos H., Larrea-Gallegos G., & Vázquez-Rowe I. (2017). Combining operational research and Life Cycle Assessment to optimize municipal solid waste collection in a district in Lima (Peru). J. Clean. Prod., vol. 156, pp. 589–603.
7. Kabir, G., and Sadiq, R. (2021). Hybrid optimization model for waste collection routing using genetic algorithms and neural networks. Journal of Cleaner Production, 293, 126147.
8. Marković, G., Vesković, S., Tanasijević, M., and Marinković, D. (2021). A hybrid approach for solving the vehicle routing problem in waste collection. Waste Management & Research, 39(1), 85-94.
9. Melo A. B., Oliveira A. M., Souza D. S. D., & Cunha M. J. D. (2017). Optimization of Garbage Collection Using Genetic Algorithm. IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), pp. 672–677.
10. Sumangala Prabhu, H., Bhat, V., Rao, V.S. (2020). Smart Waste Disposal System. In: George, V., Roy, B. (eds) Advances in Control Instrumentation Systems. Lecture Notes in Electrical Engineering, vol 660. Springer, Singapore. https://doi.org/10.1007/978-981- 15-4676-1_13
11. Xue, W. & Cao, K. (2016). Optimal routing for waste collection: a case study in Singapore. Int. J. Geogr. Inf. Sci., vol. 30, no. 3, pp. 554–572.
12. Zhang, J., and Wang, X. (2020). Socially equitable waste collection route planning. Transportation Research Part D: Transport and Environment, 81, 102283.