An efficient and general approach for the joint order batching and picker routing problem

Abstract

Picking is the process of retrieving products from inventory. It is mostly done manually by dedicated employees called pickers and is considered the most expensive of warehouse operations. To reduce the picking cost, customer orders can be grouped into batches that are then collected by traveling the shortest possible distance.This work presents an exponential linear programming formulation to tackle the joint order batching and picker routing problem. Variables, or columns, are related to the picking routes in the warehouse. Computing such routes is generally an intractable routing problem and relates to the well known traveling salesman problem (TSP). Nonetheless, the rectangular warehouse's layouts can be used to eciently solve the corresponding TSP and take into account in the development of an ecient subroutine, called oracle. We therefore investigate whether such an oracle allows for an eective exponential formulation.Experimented on a publicly available benchmark, the algorithm proves to be very eective. It improves many of the best known solutions and provides very strong lower bounds. Finally, this approach is applied to another industrial case to demonstrate its interest for this eld of application.

Practical factors in order picking planning: state-of-the-art classification and review

“…Safety included as constraint is necessary to create fea-sible routes and accurately model practice (Ballestín, Pérez, and Quintanilla 2017). Different variants of safety constraints have been proposed in literature, including penalising vehicle turning (C ¸elik and Süral 2016), prohibiting trucks moving backwards (Chabot et al 2018), forcing horizontal movements at ground level (Chabot et al 2018), limiting the number of pick vehicles working concurrently in a pick aisle (Ballestín, Pérez, and Quintanilla 2017;Van Gils et al 2019b;Chen, Xu, and Wei 2019), and forcing one-way travel directions (Briant et al 2020).…”

“…Despite opportunities to automate the order picking process (Bozer and Aldarondo 2018;Lee and Murray 2019;Jaghbeer, Hanson, and Johansson 2020), most dominant order picking systems in practice are still picker-to-part systems (De Koster, Le-Duc, and Roodbergen 2007;Calzavara et al 2017;Van Gils et al 2019a). High investment costs and the risk of interruptions in the order picking process during the implementation phase of automated systems may still discourage the use of such systems in practice (Briant et al 2020). Furthermore, picker-to-part systems still outperform robots on flexibility as humans proved to react better to unexpected changes in the process, are flexible with respect to capacity, and can retrieve a large variety of products (Van Gils et al 2019b).…”

Sequencing and routing in a large warehouse with high degree of product rotation

“…More in detail, the SRP for picking activities only is a well-studied topic in the scientific literature, displaying an increasing trend of interest over the last decade (Masae et al 2020). The most recent contributions focus on realistic aspects such as particular layout designs (Mowrey and Parikh 2014;Scholz et al 2016;Boysen et al 2017;Weidinger et al 2019;Briant et al 2020), congestion issues (Pan and Wu 2012;Chen et al 2013Chen et al , 2016, workers comfort (Grosse et al 2015) and dynamic modification of list of operations (Lu et al 2016;De Santis et al 2018). As opposed, Gómez-Montoya et al (2020) is the only contribution addressing exclusively a putaway SRP.…”

Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering

“…Such problems that cannot be expressed as MAPF include situations where agents have multiple goals so that instead of reaching single goal location agents need to perform a round-trip to service a set of goals. Many real-life applications requires that agents perform certain task at each of multiple goal locations such as performing maintenance or pickup operation (Pansart, Catusse, and Cambazard 2018;Briant et al 2020).…”