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A hybrid firefly and particle swarm optimization algorithm with local search for the problem of municipal solid waste collection: a real-life example

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Abstract

The issue of managing waste in rapidly growing urban areas has been a major problem for local administrations. One of the most critical issues in waste management is the collection and transportation of solid waste, which are both costly and difficult to address. The collection of the waste through the shortest route, at the lowest cost and in the fastest way is a major vehicle routing problem. This study addresses the problem of collecting waste in a district in the province of Şanlıurfa. To solve the problem in question, it proposes a hybrid firefly and particle swarm optimization algorithm developed using local search. The results revealed that the proposed algorithm provided 31% better outcomes than those obtained in the real-life case, 10% better than those of the geographic information system, and 5% better than those of a linear programming model.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The author is grateful to Mr. Onur Rızvanoğlu, Assoc. Dr. Mustafa Ulukavak and Prof. Dr. Mehmet İrfan Yeşilnacar for his valuable assistance and contributions in compiling field data and using geographic information system information.

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  1. Department of Industrial Engineering, Engineering Faculty, Harran University, Şanlıurfa, Turkey

    Serkan KAYA

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KAYA, S. A hybrid firefly and particle swarm optimization algorithm with local search for the problem of municipal solid waste collection: a real-life example. Neural Comput & Applic 35, 7107–7124 (2023). https://doi.org/10.1007/s00521-022-08173-6

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