Online Large-scale Garbage Collection Scheduling: A Divide-and-conquer Approach

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...

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Bibliographic Details
Published in:Proceedings - International Conference on Parallel and Distributed Systems pp. 395 - 402
Main Authors: Bian, Yixiang, Zhu, Hongzi, Lou, Ziyang
Format: Conference Proceeding
Language:English
Published: IEEE 01.01.2023
Subjects:
agglomerative hierarchical clustering algorithm
capacitated vehicle routing problem
Clustering algorithms
Complexity theory
Costs
Indexes
Large-scale garbage collection problem
Scheduling
Urban areas
Vehicle routing
ISSN:2690-5965
Online Access:Get full text
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Summary: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.
ISSN:2690-5965
DOI:10.1109/ICPADS56603.2022.00058