4.6 Article

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

Journal

NEURAL COMPUTING & APPLICATIONS
Volume 35, Issue 9, Pages 7107-7124

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00521-022-08173-6

Keywords

Vehicle routing; Firefly algorithm; Particle swarm optimization; Waste management

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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. This study addresses the problem of collecting waste in a district in the province of Sanliurfa. 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.
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 Sanliurfa. 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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