A Two-stage heuristic framework for location-arc routing optimization for a fleet of street sweepers

Effective street sweeping is vital in urban waste management, contributing significantly to city cleanness and public satisfaction. Yet many cities rely on simplistic allocation schemes that may lead to inefficiencies. This paper addresses the challenge of designing an effective street sweeper fleet management system, combining optimal decisions of depot provision and placement, fleet size, and sweeper routing. We formulated the problem as location-arc routing problem and studied the single depot version. We proposed Two-stage heuristic framework and implemented two solution methods, namely (1) a Two-stage K-medoids clustering combined with Path-Scanning and (2) an Iterated Heuristic with Path-Scanning. Computational experiments demonstrate the effectiveness of our approach in solving real-world street sweeper fleet management design problems, offering promising insights for improving urban waste management system.

I. Introduction

Street sweeping serves as a pivot in the broader framework of urban infrastructure management, offering tangible benefits in terms of environmental sustainability, public health, and transport efficiency [1]. As such the design and implementation of an efficient street sweeper fleet management system warrant careful consideration to maximize its social and economical impacts.