Abstract
Municipal solid waste management is now a global concern and needs to be addressed with proper technological innovations. In this study, a model has been developed using analytical hierarchy process, group method of data handling and artificial neural network to determine optimum time within which the collection of municipal solid waste (MSW) during each visit by each type of waste collection vehicle should be completed; this will economize the collection phase of MSW. A case study was conducted on Agartala Municipality situated in north-eastern part of India. The computed optimum route length in terms of time is 3.84 and 2.75 h for 14 and 8 m3 garbage compactor, respectively. Adoption of these optimum time estimates will lead to a cost-effective SWM as all the garbage compactors need not have to work in more than one shift, leading to a huge savings in fuel and labour cost.
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The authors want to acknowledge Agartala Municipal Corporation and Urban Development Department, Agartala, Tripura, India, for their consistent help and assistance with all available data and valuable suggestions.
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Purkayastha, D., Majumder, M., Chakrabarti, S. (2019). Municipal Solid Waste Collection Time Optimization Using AHP, GMDH and ANN. In: Kalamdhad, A., Singh, J., Dhamodharan, K. (eds) Advances in Waste Management . Springer, Singapore. https://doi.org/10.1007/978-981-13-0215-2_4
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DOI: https://doi.org/10.1007/978-981-13-0215-2_4
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