This paper investigates a waste collection problem with the consideration of midway disposal pattern. An artificial bee colony (ABC)-based hybrid approach is developed to handle this problem, in which the hybrid ABC algorithm is proposed to generate the better optimum-seeking performance while a heuristic procedure is proposed to select the disposal trip dynamically and calculate the carbon emissions in waste collection process. The effectiveness of the proposed approach is validated by numerical experiments. Experimental results show that the proposed hybrid approach can solve the investigated problem effectively. The proposed hybrid ABC algorithm exhibits a better optimum-seeking performance than four popular metaheuristics, namely a genetic algorithm, a particle swarm optimization algorithm, an enhanced ABC algorithm and a hybrid particle swarm optimization algorithm. It is also found that the midway disposal pattern should be used in practice because it reduces the carbon emission at most 7.16% for the investigated instances.

An artificial bee colony-based hybrid approach for waste collection problem with midway disposal pattern / Wei, Qu; Guo, Zhaoxia; Chuin Lau, Hoong; He, Zhenggang. - In: APPLIED SOFT COMPUTING. - ISSN 1568-4946. - STAMPA. - 76:(2019), pp. 629-637. [10.1016/j.asoc.2018.12.033]

An artificial bee colony-based hybrid approach for waste collection problem with midway disposal pattern

Qu Wei;
2019

Abstract

This paper investigates a waste collection problem with the consideration of midway disposal pattern. An artificial bee colony (ABC)-based hybrid approach is developed to handle this problem, in which the hybrid ABC algorithm is proposed to generate the better optimum-seeking performance while a heuristic procedure is proposed to select the disposal trip dynamically and calculate the carbon emissions in waste collection process. The effectiveness of the proposed approach is validated by numerical experiments. Experimental results show that the proposed hybrid approach can solve the investigated problem effectively. The proposed hybrid ABC algorithm exhibits a better optimum-seeking performance than four popular metaheuristics, namely a genetic algorithm, a particle swarm optimization algorithm, an enhanced ABC algorithm and a hybrid particle swarm optimization algorithm. It is also found that the midway disposal pattern should be used in practice because it reduces the carbon emission at most 7.16% for the investigated instances.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2722837
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