Minimizing Solid Waste Collection Routes Using Ant Colony Algorithm: A Case Study in Gaziantep District

Yıl 2021, , 29 - 47, 23.06.2021

Serap Seçkiner , Amanuel Moges Shumye Sena Geçer

https://doi.org/10.26650/JTL.2021.894265

Öz

This paper proposes an ant colony optimization algorithm for a capacitated vehicle routing problem to determine the shortest waste collection and transportation route covered by a waste collection truck in the Şahinbey municipality of Gaziantep/Turkey. The real-case problem concerns a capacity-restricted garbage compactor truck that collects and transports waste from 349 residential waste containers located in 148 collection points. Possible solutions obtained from the ant colony algorithm were compared with mixed-integer programming model solutions. The results of the proposed ant colony optimization algorithm showed that our model yields a 28% reduction in the total daily traveled distances and energy savings against existing consumption. The new solution also cuts the current annual waste collection and transportation expenditure per vehicle by 30%. It is shown that a considerably shorter route distance obtained in the algorithmic solution helps to reduce air pollution from the infamously inefficient garbage collection trucks. Eventually, the new route will considerably reduce labor costs, the high price of fuel, machinery and equipment maintenance as well as environmental pollution, because garbage compactor trucks are one of the least efficient vehicles on the road.

Anahtar Kelimeler

Solid waste management, Route optimization, Capacitated traveling salesman problem, Ant colony optimization, Mixed-integer linear programming

Kaynakça

• Abdallah, M. Talib, M.A. Feroz, S., Nasir, Q. Abdalla, H. and Mohfood, B. (2020). Artificial intelligence applications in solid waste management: A systematic research review. Waste Management, 109: 231-246.
• Bilgi Ö. (2008). Solid Waste Management in Turkey. GSI Articletter, 32, Fall 2011.
• Beijoco, F. Semião, V. Zsidgraiová, Z. (2011). Optimization of a municipal solid waste collection and transportation system. https://www.semanticscholar.org/paper/optimization-of-a-municipal-solid-waste-collection-beijoco-semião/8c0c39263e12949bf94247b7b32ed2522091a868. pdf adresinden erişildi.
• Bhambulkar, A.V. (2011). Municipal Solid Waste Collection Routes Optimized with ARC GIS Network Analyst. International Journal Of Advanced Engineering Sciences And Technologies, 11(1): 202-207.
• Chen, J. (2016) Parameters Evaluation of Colony Algorithm based on TSP. Rev. Téc. Ing. Univ. Zulia, 39 (4): 121-126.
• Choroś K., Siemiński A. (eds) (2013) Multimedia and Internet Systems: Theory and Practice. Advances in Intelligent Systems and Computing, Springer, Berlin, Heidelberg. 183: 143-153.
• Dorigo, M. Ant Colony Optimization. Scholarpedia, 2(3): 1462, 2007.http://www.scholarpedia.org/article/Ant_colony_optimization. Adresinden erişildi.
• Dorigo M. Stützle, T. (2004). Ant colony optimization, A Bradford Book, The MIT Press, Cambridge, Massachusetts.
• Das, S. Bhattacharyya, B.K. (2015). Optimization of municipal solid waste collection and transportation routes, vol. 43,pp. 9-18, September.
• Gaertner, DClark, K. (2005). On Optimal Parameters for Ant Colony Optimization Algorithms,’’ In Proc. International Conference on Artificial Intelligence.
• Gören S, and Özdemir F., (2011). Regulation of waste and waste management in Turkey Waste Management&Research, 29: 433.
• Hannan, M.A. Akhtar, M. Begum, R.A. Basri, H. Hussain, A. Scavino, E. (2018). Capacitated Vehicle-Route Problem Model for Scheduled Solid Waste Collection and Route Optimization Using PSO Algorithm. Waste Management. 71: 31.
• Hanna, M.A., Hossain Lipu H.S., Akhtar M., Begum R.A., Al Mamun A. Hussain A., Mia M.S., Basri, H., (2020) Solid waste collection optimization objectives, constraints, modeling approaches, and their challenges toward achieving sustainable development goals. Journal of Cleaner Production, Vol: 277, 123557.
• Islam, R. Rahman, M. S. (2012). An ant colony optimization algorithm for waste collection vehicle routing with time windows driver rest period and multiple disposal facilities,’’In Proc. Informatics Electronics & Vision (ICIEV) International Conference on IEEE. 774-779.
• Karadimas, N.V. Papatzelou, K. Loumos, V.G. (2007). Genetic Algorithms for Municipal Solid Waste Collection and Routing Optimization. International Federation for Information Processing Digital Library; Artificial Intelligence and Innovations,: from Theory to Applications. 247: 223-232.
• Köse Ö.H, Ayaz S, and Köroglu B (2007). Waste Management in Turkey: National Regulations and Evaluation of Implementation Results. Turkish Court of Accounts, Performance Audit Report 5181/1: 75.
• Liu, L., Liao W. (2021) Optimization and profit distribution in a two-echelon collaborative waste collection routing problem from economic and environmental perspective, Waste Management. Vol: 120, pp. 400-414.
• Mamashli, Z., Javadian N., (2020) Sustainable design modifications municipal solid waste management network and better optimization for risk reduction analyses, Journal of Cleaner Production, Vol: 279, 123824.
• Mojtahedi M., Fathollahi-Fard Amir M., Moghaddam, R. T., Newton S., (2021) Sustainable vehicle routing problem for coordinated solid waste Management, Journal of Industrial Information Integration, Vol: 23, 100220.
• Nguyen XC., Nguyen TTH., La DD., Kumar G., Rene E.R., Nguyen D.D., Chung SW., Chung WJ., Nguyen XH., Nguyen VK., (2021). Development of machine learning based models to forecast solid waste generation in residential areas: A case study from Vietnam, Resources, Conservation & Recycling, 167: 105381.
• Siemiński A., (2013). Ant Colony Optimization Parameter Evaluation. Multimedia and Internet Systems: Theory and Practice. 143-153.
• Talebbeydokhti, N. Amiri, H. Shahraki, M.H. Azadi S., Ghahfarokhi, S.G. (2013) ‘‘Optimization of Solid Waste Collection and Transportation System by Use of the TransCAD: A Case Study’’, ArchHyg Sci; 2(4): 150-7.
• Tavares, G. Zsigraiova, Z. Semiao, V. Carvalho, M.G. (2009). Optimization of MSW collection routes for minimum fuel consumption using 3D GIS modeling. Waste Management. 29(3): 1176-1185.