The storage location assignment and picker routing problem: A generic branch-cut-and-price algorithm

The Storage Location Assignment Problem (SLAP) and the Picker Routing Problem (PRP) have received significant attention in the literature due to their pivotal role in the performance of the Order Picking (OP) activity, the most resource-intensive process of warehousing logistics. The two problems are traditionally considered at different decision-making levels: tactical for the SLAP, and operational for the PRP. However, this paradigm has been challenged by the emergence of modern practices in e-commerce warehouses, where decisions are more dynamic. This shift makes the integrated problem, called the Storage Location Assignment and Picker Routing Problem (SLAPRP), pertinent to consider. Scholars have investigated several variants of the SLAPRP, including different warehouse layouts and routing policies. Nevertheless, the available computational results suggest that each variant requires an ad-hoc formulation. Moreover, achieving a complete integration of the two problems, where the routing is solved optimally, remains out of reach for commercial solvers, even on trivial instances. In this paper, we propose an exact solution framework that addresses a broad class of variants of the SLAPRP, including all the previously existing ones. This paper proposes a Branch-Cut-and-Price framework based on a novel formulation with an exponential number of variables, which is strengthened with a novel family of non-robust valid inequalities. We have developed an ad-hoc branching scheme to break symmetries and maintain the size of the enumeration tree manageable. Computational experiments show that our framework can effectively solve medium-sized instances of several SLAPRP variants and outperforms the state-of-the-art methods from the literature.

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Publication Details

Journal
European Journal of Operational Research
Published
2025-06-16
DOI
https://doi.org/10.1016/j.ejor.2025.05.041
Citations
1
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
1.24

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article

The storage location assignment and picker routing problem: A generic branch-cut-and-price algorithm

Diego Cattaruzza, Thibault Prunet, Nabil Absi
1 citations
European Journal of Operational Research
Advanced Manufacturing and Logistics Optimization
1.24
article

The storage location assignment and picker routing problem: A generic branch-cut-and-price algorithm

Diego Cattaruzza, Thibault Prunet, Nabil Absi
article en
1 citations

Abstract

The Storage Location Assignment Problem (SLAP) and the Picker Routing Problem (PRP) have received significant attention in the literature due to their pivotal role in the performance of the Order Picking (OP) activity, the most resource-intensive process of warehousing logistics. The two problems are traditionally considered at different decision-making levels: tactical for the SLAP, and operational for the PRP. However, this paradigm has been challenged by the emergence of modern practices in e-commerce warehouses, where decisions are more dynamic. This shift makes the integrated problem, called the Storage Location Assignment and Picker Routing Problem (SLAPRP), pertinent to consider. Scholars have investigated several variants of the SLAPRP, including different warehouse layouts and routing policies. Nevertheless, the available computational results suggest that each variant requires an ad-hoc formulation. Moreover, achieving a complete integration of the two problems, where the routing is solved optimally, remains out of reach for commercial solvers, even on trivial instances. In this paper, we propose an exact solution framework that addresses a broad class of variants of the SLAPRP, including all the previously existing ones. This paper proposes a Branch-Cut-and-Price framework based on a novel formulation with an exponential number of variables, which is strengthened with a novel family of non-robust valid inequalities. We have developed an ad-hoc branching scheme to break symmetries and maintain the size of the enumeration tree manageable. Computational experiments show that our framework can effectively solve medium-sized instances of several SLAPRP variants and outperforms the state-of-the-art methods from the literature.

European Journal of Operational ResearchVol. 327(3)
University of Udine (IT), Centre National de la Recherche Scientifique (FR), École nationale des ponts et chaussées (FR), University of Clermont Auvergne (FR), Centre de Recherche en Informatique (FR), CERMICS (FR), Université Mohammed VI Polytechnique (MA), Clermont Université (FR), École Centrale de Lille (FR)
Agence Nationale de la Recherche
Openalex Percentile: Top 18%
Advanced Manufacturing and Logistics Optimization
1.24
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