Abstract
Designing optimization models and meta-heuristic algorithms for minimization of traveling routes of vehicles in solid waste collection has been gaining interest in environmental modeling. The computer models and methods are useful to bring out specific strategies for prevention and precaution of possible disasters that could be foreseen worldwide. This paper proposes a new Spatial Geographic Information System (GIS)-based Genetic Algorithm for optimizing the route of solid waste collection. The proposed algorithm, called SGA, uses a modified version of the original Dijkstra algorithm in GIS to generate optimal solutions for vehicles. Then, a pool of solutions, which are optimal routes of all vehicles, is encoded in Genetic Algorithm. It is iteratively evolved to a better one and finally to the optimal solution. Experiments on the case study at Sfax city in Tunisia are performed to validate the performance of the proposal. It has been shown that the proposed method has better performance than the practical route and the original Dijkstra method.
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Ali M, Thanh ND, Van Minh N (2018) A neutrosophic recommender system for medical diagnosis based on algebraic neutrosophic measures. Appl Soft Comput. https://doi.org/10.1016/j.asoc.2017.10.012
Awasare SD, Sutar AS (2015) Review Article Solid Waste Management & GIS, 5, 22–28
Bartolozzi I, Baldereschi E, Daddi T, Iraldo F (2018) The application of life cycle assessment (LCA) in municipal solid waste management: a comparative study on street sweeping services. J Clean Prod 182:455–465
Benjamin AM, Beasley JE (2010) Metaheuristics for the waste collection vehicle routing problem with time windows, driver rest period and multiple disposal facilities. Comput Oper Res 37:2270–2280
Buhrkal K, Larsen A, Ropke S (2012) The waste collection vehicle routing problem with time windows in a City logistics context. Procedia - Soc Behav Sci 39:241–254
Cheng G, Huang G, Dong C, Xu Y, Chen X, Chen J (2017a) Distributed mixed-integer fuzzy hierarchical programming for municipal solid waste management. Part I: system identification and methodology development. Environ Sci Pollut Res 24(8):7236–7252
Cheng G, Huang G, Dong C, Xu Y, Chen J, Chen X, Li K (2017b) Distributed mixed-integer fuzzy hierarchical programming for municipal solid waste management. Part II: scheme analysis and mechanism revelation. Environ Sci Pollut Res 24(9):8711–8721
Cruz YXD, Chirva JAP, & Santana ERL, (2015) A mixed integer optimization model to design a selective collection routing problem for domestic solid waste. In engineering applications-international congress on engineering (WEA), 2015 workshop on (pp. 1-5). IEEE
Das S, Bhattacharyya BK (2015) Optimization of municipal solid waste collection and transportation routes. Waste Manag 43:9–18
Desai SN, Shah M, Zaveri P (2018) Route optimisation for solid waste management using ArcGIS network analyst: a review. Int J Eng Technol Sci Res 5(1):137–140
Ding Z, Zhu M, Tam VW, Yi G, Tran CN (2018) A system dynamics-based environmental benefit assessment model of construction waste reduction management at the design and construction stages. J Clean Prod 176:676–692
Elsayed SM, Sarker RA, Essam DL (2014) A new genetic algorithm for solving optimization problems. Eng Appl Artif Intell 27:57–69
Giap CN, Son LH, & Chiclana F (2018) Dynamic structural neural network. J Intel Fuzzy Syst, (preprint), 1-12
Habitat UN (2010) Solid waste management in the world’s cities. Water and Sanitation in the Worlds Cities
Han B, Liu YT, Wu JH, Feng YC (2018) Characterization of industrial odor sources in Binhai new area of Tianjin, China. Environ Sci Pollut Res 25(14):14006–14017
Horodytska O, Valdés FJ, Fullana A (2018) Plastic flexible films waste management–a state of art review. Waste Manag 77:413–425. https://doi.org/10.1016/j.wasman.2018.04.023
Hemanth DJ, Anitha J, Popescu DE, Son LH (2018a) A modified genetic algorithm for performance improvement of transform based image steganography systems. J Intell Fuzzy Sys, (Preprint) 1–13. https://doi.org/10.3233/JIFS-169580
Hokkanen J, Salminen P (1997) Choosing a solid waste management system using multicriteria decision analysis. Eur J Oper Res 98:19–36
Hoornweg D, Tata BP (2012) WHAT a WASTE : a global review of solid waste management, urban development series;knowledge papers no. 15. World Bank, Washington, DC. © World Bank
Huang SH, Lin PC (2015) Vehicle routing–scheduling for municipal waste collection system under the “keep trash off the ground” policy. Omega 55:24–37
Hemanth DJ, Anitha J, Son LH (2018b) Brain signal based human emotion analysis by circular back propagation and Deep Kohonen Neural Networks. Comput Electr Eng 68:170-180
Hickman J, Hassel D, Joumard R, Samaras Z, Sorenson S (1999) Methodology for calculating transport emissions and energy consumption. Doi https://trid.trb.org/view/707881
Jiao W, Min Q, Cheng S, Li W (2013) The waste absorption footprint (WAF): a methodological note on footprint calculations. Ecol Indic 34:356–360
Karadimas NV, Kolokathi M, Defteraiou G, Loumos V (2007) Ant Colony system vs ArcGIS network analyst: the case of municipal solid waste collection. 5th WSEAS Int. Conf. Environ. Ecosyst. Dev. 128–134
Khan D, Samadder SR (2014) Municipal solid waste management using geographical information system aided methods: a mini review. Waste Manag Res 32:1049–1062
Kholod N, Evans M, Gusev E, Yu S, Malyshev V, Tretyakova S, Barinov A (2016) A methodology for calculating transport emissions in cities with limited traffic data: case study of diesel particulates and black carbon emissions in Murmansk. Sci Total Environ 547:305–313
Louati A, Son LH , Chabchoub H (2018) Smart routing for municipal solid waste collection: a heuristic approach. Journal of ambient intelligence and humanized computing, 1-20
Malakahmad A, Bakri PM, Mokhtar MRM, Khalil N (2014) Solid waste collection routes optimization via GIS techniques in Ipoh City. Malaysia Procedia Eng 77:20–27
Murata T, & Ishibuchi H (1994) Performance evaluation of genetic algorithms for flowshop scheduling problems. In evolutionary computation, 1994. IEEE world congress on computational intelligence., proceedings of the first IEEE conference on (pp. 812-817). IEEE
Onan K, Ülengin F, Sennaroğlu B (2015) An evolutionary multi-objective optimization approach to disaster waste management: a case study of Istanbul, Turkey. Expert Syst Appl 42(22):8850–8857
Sanjeevi V, Shahabudeen P (2016) Optimal routing for efficient municipal solid waste transportation by using ArcGIS application in Chennai, India. Waste Manag Res 34(1):11–21
Son LH (2014) Optimizing municipal solid waste collection using chaotic particle swarm optimization in GIS based environments: a case study at Danang city. Vietnam Expert Syst Appl 41:8062–8074
Son LH, Louati A (2016) Modeling municipal solid waste collection: a generalized vehicle routing model with multiple transfer stations, gather sites and inhomogeneous vehicles in time windows. Waste Manag 52:34–49
Son LH, Chiclana F, Kumar R, Mittal M, Khari M, Chatterjee JM, Baik SW (2018) ARM–AMO: an efficient association rule mining algorithm based on animal migration optimization. Knowl-Based Syst 154:68–80
Singh K, Singh K, Son LH, Aziz A (2018) Congestion control in wireless sensor networks by hybrid multi-objective optimization algorithm. Comput Netw 138:90–107
Tam NT, Hai DT, Son LH, Vinh LT (2018) Improving lifetime and network connections of 3D wireless sensor networks based on fuzzy clustering and particle swarm optimization. Wirel Netw 24(5):1477–1490
Tavares G, Zsigraiova Z, Semiao V, Carvalho MG (2009) Optimisation of MSW collection routes for minimum fuel consumption using 3D GIS modelling. Waste Manag 29:1176–1185
Thong PH, Son LH (2016) A novel automatic picture fuzzy clustering method based on particle swarm optimization and picture composite cardinality. Knowl-Based Syst 109:48–60
Wilson DC, Rodic L, Scheinberg A, Velis CA, Alabaster G (2012) Comparative analysis of solid waste management in 20 cities. Waste Manag Res 30(3):237–254
Yadav P, Samadder SR (2018) Environmental impact assessment of municipal solid waste management options using life cycle assessment: a case study. Environ Sci Pollut Res 25(1):838–854
Yu H, Solvang WD, Li S (2015) Optimization of long-term performance of municipal solid waste management system: a bi-objective mathematical model. Int J ENERGY Environ 6:153–164
Zsigraiova Z, Semiao V, Beijoco F (2013) Operation costs and pollutant emissions reduction by definition of new collection scheduling and optimization of MSW collection routes using GIS. The case study of Barreiro, Portugal. Waste Manag 33:793–806
Acknowledgements
The author (Le Hoang Son) would like to thank the Ton Duc Thang University for sponsoring this research. This work belongs to the PhD thesis of Louati Amal under the cooperation between the University of Sfax, Tunisia, and Vietnam National University, Hanoi.
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Amal, L., Son, L.H. & Chabchoub, H. SGA: spatial GIS-based genetic algorithm for route optimization of municipal solid waste collection. Environ Sci Pollut Res 25, 27569–27582 (2018). https://doi.org/10.1007/s11356-018-2826-0
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DOI: https://doi.org/10.1007/s11356-018-2826-0