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A hybrid metaheuristic for smart waste collection problems with workload concerns
Computers & Operations Research ( IF 4.6 ) Pub Date : 2021-08-20 , DOI: 10.1016/j.cor.2021.105518
Diana Jorge 1, 2 , António Pais Antunes 1 , Tânia Rodrigues Pereira Ramos 3 , Ana Paula Barbosa-Póvoa 3
Affiliation  

In this paper, a hybrid metaheuristic is developed to solve the smart waste collection problem with workload concerns. It is composed by: (i) a look-ahead heuristic aiming at deciding the days in which collection is necessary and which bins need to be collected (must-go) considering the present bin fill levels and future bin fill level predictions; and (ii) a simulated annealing/neighborhood search algorithm to choose the bins that are profitable to collect and the best route(s) to visit the bins. This algorithm was developed to find solutions within a relatively short amount of time (we considered two hours as reference), as required for practical operations. The proposed hybrid metaheuristic is applied to randomly-generated test instances of sizes up to 500 bins and to a real case study of recyclables collection, leading to results that demonstrate its effectiveness and usefulness in practice when dealing with large-size instances. For the real case study, involving a major waste management company in Portugal, the profit achieved by the hybrid metaheuristic is at least 45% higher than the profit obtained by the company, and, at the same time, compliance with maximum shift duration and route workload balance is clearly better when the metaheuristic is used than in current operations.



中文翻译:

具有工作量问题的智能垃圾收集问题的混合元启发式算法

在本文中,开发了一种混合元启发式算法来解决具有工作量问题的智能垃圾收集问题。它由以下部分组成: (i) 前瞻启发式算法,旨在考虑当前仓位填充水平和未来仓位填充水平预测,决定需要收集的天数以及需要收集(必须进行)的仓位;(ii) 模拟退火/邻域搜索算法来选择有利可图的垃圾箱和访问垃圾箱的最佳路线。该算法旨在根据实际操作的需要,在相对较短的时间内(我们以两小时为参考)找到解决方案。所提出的混合元启发式应用于随机生成的最大 500 个垃圾箱的测试实例和可回收物收集的真实案例研究,导致在处理大型实例时证明其在实践中的有效性和有用性的结果。对于涉及葡萄牙一家大型废物管理公司的真实案例研究,混合元启发式实现的利润至少比公司获得的利润高 45%,同时符合最大班次持续时间和路线当使用元启发式时,工作负载平衡显然比当前操作更好。

更新日期:2021-08-27
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