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Allocation of Bins in Urban Solid Waste Logistics System

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 741))

Abstract

Management of solid waste is a very crucial and difficult work for any municipal corporation across the world. Mismanaged solid wastes have very negative impact on the environment which is a serious issue for many developing countries like India. Municipal solid waste management (MSWM) consists of multidisciplinary activities which include forecasting generation, storage and collection, transportation, treatment, and waste disposal. Of all these activities, waste collection and transportation account for 50–70% of total cost of the system. At present, due to the insufficient number of waste bins and their poor allocations, our society is having a littering habit of waste disposal which is hazardous for the environment. India generates 133,760 metric tons of MSW per day but due to poor waste collection system only 91,152 metric ton per day gets collected and remaining waste goes to low-lying urban area. It has been estimated that dumping of waste requires 212,752 cubic meter of space every day which is a very critical issue because there is limitation in availability of space and waste generation is increasing every year at 5%. In this paper we have formulated a MILP model for the calculation of total number of bin required in any site for different types of waste and we have proposed a method for the allocation of bins within the site such that it able to capture the total waste of the site. For solving the MILP model CPLEX software is used and for allocation of bins ArcGIS software.

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Acknowledgements

The authors acknowledge the support of Bilaspur Municipal Corporation for providing the necessary data and having discussions over present situation and feasibility of the proposed model.

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Correspondence to P. Rathore .

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Rathore, P., Sarmah, S.P. (2019). Allocation of Bins in Urban Solid Waste Logistics System. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_47

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