Urbanization and population growth have resulted in a significant increase in the amount of generated construction and demolition (C&D) waste worldwide. Improper C&D waste management has led to a tremendous landfilled C&D waste, which has placed a great concern over its adverse impacts on the environment and natural resources. Appropriate C&D waste recycling mechanism as a remedial action saves our resources from deterioration, which can be guaranteed through a systematic apportion of the construction projects to C&D waste recycling facilities. Previous studies in waste collection routing problem have almost exclusively assumed that parameters are deterministic; 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.

城市化和人口增长导致全世界产生的建筑和拆迁（C＆D）废物数量显着增加。拆建废料管理不当导致大量填埋拆建废料，这对其环境和自然资源的不利影响引起了极大的关注。适当的C＆D废物回收机制作为补救措施，可以节省资源，避免资源退化，这可以通过将建设项目系统分配给C＆D废物回收设施来保证。先前有关废物收集路由问题的研究几乎完全假设参数是确定性的；但是，与废物收集路线相关的不确定性使确定性模型不适用于现实生活中的系统。为了解决这个问题，这项研究提出了一种基于集成模拟优化方法的新型模拟方法，其中应用了一种有效的混合遗传算法（GA），以优化从建筑项目到回收设施的C＆D废物收集的车辆路线规划。与现有的众所周知的方法进行比较分析，以代表所提出方法的强度和有效性。结果证明了所提出的模拟算法的高性能。这项研究还受益于澳大利亚悉尼的建筑项目分配给回收设施的案例，以便进行更好的评估。这项研究以更广泛，更精确的方式阐明了优化未来废物收集问题的方法，从而为学术界做出了巨大贡献。与此同时，