Improving construction and demolition waste collection service in an urban area using a simheuristic approach: A case study in Sydney, Australia

Abstract Urbanization and population growth have resulted in a significant increase in the amount of generated construction and demolition (CD however, uncertainty associated with waste collection routing makes deterministic models inapplicable to real-life systems. To tackle this problem, this research proposes a novel simheuristic based on an integrated simulation-optimization approach, in which an efficient hybrid Genetic Algorithm (GA) is applied in order to optimize vehicle route planning for C&D waste collection from construction projects to recycling facilities. A comparative analysis with existing well-known approaches is performed to represent the strength and effectiveness of the proposed approach. The results demonstrate high performance of the proposed simheuristic algorithm. This study has also benefited from a real case of construction projects apportion to recycling facilities in Sydney, Australia for better evaluation. This research strongly contributes to academics by lighting up the ways to optimize future waste collection problems in a wider range and more precise manner. Meanwhile, this study recommends to C&D waste decision makers and practitioners to allocate generated C&D waste to recycling facilities precisely with respect to the capacity of produced C&D waste, capacity of recycling facilities, distances, and vehicle capacities.

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