Work

Effective GA approach for municipal solid waste collection: dynamic capacitated vehicle routing in smart cities

Year: 2022

Type: article

Abstract: Currently, municipal solid waste (MSW) collection is based on ineffective and inflexible static routing models done once a day by trucks. Given a set of fixed bins distributed over a specified area, trucks move along their predefined routes to collect the bins contents. It is also revealed that logistics costs for collection and recycling represent 95% of total cost; thus, minimising total travelled distances using minimum vehicles is of a key importance. This paper presents a genetic algorithm-based solution for municipal solid waste collection and monitoring at smart cities modelled as a capacitated vehicles routing problem (CVRP). This solution adopts two crossover techniques and three mutation methods applied on the population divided into three subsets. Experimental results over various benchmarks show the effectiveness and superiority of the proposed approach in terms of runtime and solution quality. Finally, a real case study of 50 sites (49 bins + a depot) and ten trucks is deployed in the City of Baba Hassen, Algiers, Algeria.

Source: International Journal of Artificial Intelligence and Soft Computing

DOI: 10.1504/ijaisc.2022.130561

Authors: Mustapha Aouache, Ahmed Kouider, Abdelfetah Hentout, Abderraouf Maoudj

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure, Responsible consumption and production

Open Access status: hybrid

OpenAlex ID: W4366965142

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