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Optimization of municipal solid waste collection and transportation routes, through linear programming and geographic information system: a case study from Şanlıurfa, Turkey

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Abstract

Solid waste is one of the important causes of the environmental crisis that negatively impacts human health throughout the world and is fast approaching a disaster level that will pose a direct threat to human life. As with all other environmental problems, the increase in solid waste production that goes hand in hand with growing population and rising consumption has become a focus of great concern. Along with these rising levels, the investment, management and maintenance of solid waste collection and transport vehicles is seeing a continual increase in financial outlay. It is clear from the budgets of local authority solid waste management systems, 65 to 80% of which are accounted for by domestic waste, that the collection and transport of solid waste is a high-cost process and that this expenditure can be significantly reduced by the reorganisation of solid waste collection routing schedules and the minimization of collection frequency. This study demonstrates a linear programming model in order to develop an optimal routing schedule for solid waste collection and transportation, thereby reducing costs to a minimum. The neighbourhood of Veysel Karani in the Haliliye District of Şanlıurfa Province, Turkey, was specifically selected for this case study, having the suitable socio-economic and demographic variables to be representative of a metropolitan urban area. Firstly, the data regarding the municipal solid waste collection and transport routes were obtained from the local authority. Analysis and verification of these data were then performed. With the field study, these data were verified on-site, and the missing data were completed. Linear programming and geographic information system (GIS) analysis were used to determine the best route. Consequently, it is concluded that it is possible to save the route by 28% with GIS analysis and 33% with linear programming analysis according to the existing municipal solid waste collection and transportation routes.

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References

  • Akhand, A. M., Peya, J. Z., & Murase, K. (2018). Capacitated vehicle routing problem solving using adaptive sweep and velocity tentative PSO. International Journal of Advanced Computer Science and Applications, 8(12), 288–295. https://doi.org/10.14569/ijacsa.2017.081237.

    Article  Google Scholar 

  • Aydemir, E., Karagül, K., & Tokat, S. (2016). A new algorithm to the construction of the initial routes for the capacitated vehicle routing problem. Mühendislik Bilimleri ve Tasarım Dergisi. Süleyman Demirel University. https://doi.org/10.21923/jesd.60313

    Article  Google Scholar 

  • Bozyer, Z., Alkan, A., & Fığlalı, A. (2014). Cluster-first then-route based heuristic algorithm for the solution of capacitated vehicle routing problem. International Journal of Information Technologies, 7(2), 29–37.

    Google Scholar 

  • Chandran, B., & Raghavan, S. (2008). Modeling and solving the capacitated vehicle routing problem on trees. In Operations Research/ Computer Science Interfaces Series (pp. 239–261). Boston: Springer. https://doi.org/10.1007/978-0-387-77778-8_11.

    Chapter  Google Scholar 

  • Clarke, G. & Wright, J.R. (1964). Scheduling of Vehicle Routing Problem from a Central Depot to a Number of Delivery Points. Operations Research, 12, 568–581. https://doi.org/10.1287/opre.12.4.568.

    Article  Google Scholar 

  • Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management Science, 6(1), 80–91. https://doi.org/10.1287/mnsc.6.1.80.

    Article  Google Scholar 

  • Dantzig, G., Fulkerson, R., & Johnson, S. (1954). Solution of a Large-Scale Traveling-Salesman Problem. Journal of the Operations Research Society of America, 2(4), 393–410 .

  • Dincer, S. E., & Diskaya, F. (2018). A model proposal for greeen logistic management vehicle routing optimization. Beykoz Akademi Dergisi, 6(1), 29–46. https://doi.org/10.14514/byk.m.21478082.2018.6/1.29-46.

    Article  Google Scholar 

  • El Hassani, A. H., Bouhafs, L., & Koukam, A. (2008). A hybrid ant colony system approach for the capacitated vehicle routing problem and the capacitated vehicle routing problem with time windows. In T. Caric & H. Gold (Eds.), Vehicle Routing Problem (pp. 57–70). Rijeka: IntechOpen. https://doi.org/10.5772/5640.

    Chapter  Google Scholar 

  • Gajpal, Y., & Abad, P. L. (2009). Multi-ant colony system (MACS) for a vehicle routing problem with backhauls. European Journal of Operational Research, 196, 102–117. https://doi.org/10.1016/j.ejor.2008.02.025.

    Article  Google Scholar 

  • Goodchild, M. F. (1977). An evaluation of lattice solutions to the problem of corridor location. Environment and Planning A: Economy and Space, 9(7), 727–738. https://doi.org/10.1068/a090727.

    Article  Google Scholar 

  • Kirci, P. (2016). An optimization algorithm for a capacitated vehicle routing problem with time windows. Sādhanā, 41(5), 519–529. https://doi.org/10.1007/s12046-016-0488-5.

    Article  Google Scholar 

  • Lal, P., Ganapathy, L., Sambandam, N., & Vachajitpan, P. (2009). Heuristic methods for capacitated vehicle routing problem. International Journal Of Logistics And Transport, 4, 343–352.

    Google Scholar 

  • Lunkapis, J. G., Ahmad, N., Shariff, A. R. M., Mansor, S., & Mispan, R. M. (2002). GIS as decision support tool for landfills siting. University of Putra.

  • Lysgaard, J., Letchford, A. N., & Eglese, R. W. (2004). A new branch-and-cut algorithm for the capacitated vehicle routing problem. Mathematical Programming, 100(2), 423–445. https://doi.org/10.1007/s10107-003-0481-8.

    Article  Google Scholar 

  • Mazzeo, S., & Loiseau, I. (2004). An ant colony algorithm for the capacitated vehicle routing. Electronic Notes in Discrete Mathematics, 18, 181–186. https://doi.org/10.1016/j.endm.2004.06.029.

    Article  Google Scholar 

  • Mostafa, N., & Eltawil, A. (2017). Solving the heterogeneous capacitated vehicle routing problem using K-means clustering and valid inequalities. In Proceedings of the international conference on industrial engineering and operations management.

  • Nas, B., & Berktay, A. (2002). Application of geographic information systems to solve environmental problems. In 2nd geopraphical informations systems informations days: use of geographic information systems in the solution of environmental problems (pp. 1–11). İstanbul.

  • Osman, I. H. (1993). Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem. Annals of Operations Research, 41(4), 421–451. https://doi.org/10.1007/BF02023004.

    Article  Google Scholar 

  • Pala, O., & Aksaraylı, M. (2018). An ant colony optimization algorithm approach for solving multi-objective capacitated vehicle routing problem. Alphanumeric Journal, 6(1), 37–48. https://doi.org/10.17093/alphanumeric.366852.

    Article  Google Scholar 

  • Ralphs, T. K., Kopman, L., Pulleyblank, W. R., & Trotter, L. E. (2003). On the capacitated vehicle routing problem. Mathematical Programming, 94(2), 343–359. https://doi.org/10.1007/s10107-002-0323-0.

    Article  Google Scholar 

  • Reed, M., Yiannakou, A., & Evering, R. (2014). An ant colony algorithm for the multi-compartment vehicle routing problem. Applied Soft Computing Journal, 15, 169–176. https://doi.org/10.1016/j.asoc.2013.10.017.

    Article  Google Scholar 

  • Rızvanoğlu, O. (2018). Optimization of solid waste collection route: the example of Haliliye (Şanlıurfa) County. Harran University.

  • Sadek, S., El-Fadel, M., & El-Hougeiri, N. (2001). Optimizing landfill siting through GIS application. In 17th International Conference on Solid Waste Technology and Management. Philadelphia.

  • Sadek, S., El-Fadel, M., & Freiha, F. (2006). Compliance factors within a GIS-based framework for landfill siting. International Journal of Environmental Studies, 63(1), 71–86. https://doi.org/10.1080/00207230600562213.

    Article  Google Scholar 

  • Szeto, W. Y., Wu, Y., & Ho, S. C. (2011). An artificial bee colony algorithm for the capacitated vehicle routing problem. European Journal of Operational Research, 215(1), 126–135. https://doi.org/10.1016/j.ejor.2011.06.006.

    Article  Google Scholar 

  • Takes, F. W., & Kosters, W. A. (2010). Applying Monte Carlo techniques to the capacitated vehicle routing problem. In 22th Benelux Conference on Artificial Intelligence Conference. Netherlands.

  • Töreyen, G., Özdemir, İ., & Kurt, T. (2010). ArcGIS 10 Desktop Application Document. Ankara: İşlem Coğrafi Bilgi Sistemleri Mühendislik ve Eğitim Ltd. Şti.

    Google Scholar 

  • Toth, P., & Vigo, D. (2002). Models, relaxations and exact approaches for the capacitated vehicle routing problem. Discrete Applied Mathematics, 123(1), 487–512. https://doi.org/10.1016/S0166-218X(01)00351-1.

    Article  Google Scholar 

  • Venkatesan, S. R., Logendran, D., & Chandramohan, D. (2011). Optimization of capacitated vehicle routing problem using particle swarm optimization. International Journal of Engineering Science and Technology (IJEST), 3(10), 7469–7477.

    Google Scholar 

  • Wang, C. H., & Lu, J. Z. (2009). A hybrid genetic algorithm that optimizes capacitated vehicle routing problems. Expert Systems with Applications, 36(2), 2921–2936. https://doi.org/10.1016/j.eswa.2008.01.072.

    Article  Google Scholar 

  • Yalçın, P. S. (2014). New Mathematical Formulations for The Selective Travelling Salesman Problem. Başkent University.

  • Yoldaş, M. A. (2008). Examination of road classifications on highways and the typical cross sections: the case study For Eminonu-Fatih. İstanbul Technical University.

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Acknowledgements

This study was funded by Harran University Scientific Research Project coordination office (HÜBAP Project No: 16205) and owes a debt of gratitude to Haliliye Council for their unstinting help and support in the measuring of distances from within vehicles, the provision of basic maps, and the development of solid waste collection routing maps.

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Authors and Affiliations

  1. Engineering Faculty, Department of Environmental Engineering, Harran University, 63050, Şanlıurfa, Turkey

    Onur Rızvanoğlu & Mehmet İrfan Yeşilnacar

  2. Engineering Faculty, Department of Industrial Engineering, Harran University, 63050, Şanlıurfa, Turkey

    Serkan Kaya

  3. Engineering Faculty, Department of Geomatics Engineering, Harran University, 63050, Şanlıurfa, Turkey

    Mustafa Ulukavak

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  1. Onur Rızvanoğlu
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  2. Serkan Kaya
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  3. Mustafa Ulukavak
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  4. Mehmet İrfan Yeşilnacar
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Correspondence to Mehmet İrfan Yeşilnacar.

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Rızvanoğlu, O., Kaya, S., Ulukavak, M. et al. Optimization of municipal solid waste collection and transportation routes, through linear programming and geographic information system: a case study from Şanlıurfa, Turkey. Environ Monit Assess 192, 9 (2020). https://doi.org/10.1007/s10661-019-7975-1

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