Online Large-scale Garbage Collection Scheduling: A Divide-and-conquer Approach - Bian, Yixiang; Zhu, Hongzi; Lou, Ziyang (Proceedings - International Conference on Parallel and Distributed Systems, 2023)
Online garbage collection scheduling is demanding for large cities to reduce the increasing operational costs. However, the garbage collection problem is NP-complete, making the problem intractable when the number of garbage sites is large. In this paper, we first intensively investigate the garbage collection problem and derive insightful theoretical guidance for decomposing a large-scale garbage collection problem. We then propose an agglomerative hierarchical clustering algorithm, called Pie, for online large-scale garbage collection scheduling, where the original problem can be equivalently decomposed into a set of small-scale tractable sub-problems. We implement Pie which has a O(n^{2}) complexity and adopt LKH-3, the state-of the-art CVRP algorithm, as the underlying algorithm to solve sub-problems obtained by Pie. We conduct extensive trace-driven simulations on 11 real-world datasets. The results show that Pie can effectively reduce both the overall collection cost and the running time, demonstrating the efficacy of the Pie algorithm. Index Terms--Large-scale garbage collection problem, capacitated vehicle routing problem, agglomerative hierarchical clustering algorithm.