Solving the Capacitated Arc Routing Problem Using Logic‐Based Benders Decomposition

ABSTRACT In this paper, we present a new exact algorithm for solving the capacitated arc routing problem using logic‐based benders decomposition. The master problem is formulated based on variables that measure the number of deadheadings of each edge. These variables have been converted into binary form, which enables the use of both new and stronger inequalities. The subproblem is transformed into a node‐routing feasibility problem, where we exploit that the number of edge traversals is fixed, as this information is provided by the master problem. The computational results show that the proposed algorithm outperforms the current state‐of‐the‐art on about half of the classical instances, in many cases by an order of magnitude. The algorithm is also able to determine the optimal solution for a previously unsolved instance.

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Publication Details

Journal
Networks
Published
2026-10-26
DOI
https://doi.org/10.1002/net.70085
Primary Topic
Vehicle Routing Optimization Methods
Type
article
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article

Solving the Capacitated Arc Routing Problem Using Logic‐Based Benders Decomposition

Sanne Wøhlk, Michael M. Sørensen, Alexander Ingemann Lindhardt
Networks
Vehicle Routing Optimization Methods
article

Solving the Capacitated Arc Routing Problem Using Logic‐Based Benders Decomposition

Sanne Wøhlk, Michael M. Sørensen, Alexander Ingemann Lindhardt
article en

Abstract

ABSTRACT In this paper, we present a new exact algorithm for solving the capacitated arc routing problem using logic‐based benders decomposition. The master problem is formulated based on variables that measure the number of deadheadings of each edge. These variables have been converted into binary form, which enables the use of both new and stronger inequalities. The subproblem is transformed into a node‐routing feasibility problem, where we exploit that the number of edge traversals is fixed, as this information is provided by the master problem. The computational results show that the proposed algorithm outperforms the current state‐of‐the‐art on about half of the classical instances, in many cases by an order of magnitude. The algorithm is also able to determine the optimal solution for a previously unsolved instance.

Networks
Aarhus University (DK)
Openalex Percentile: Top 13%
Vehicle Routing Optimization Methods
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