Abstract
Designing an order picking system can be very complex, as several interrelated control variables are involved. We address the sizing of the storage capacity of the picking bay, the crew of pickers, and the AGV fleet, which are the most important variables from a tactical viewpoint in a parts-to-pickers system. Although order picking is a widely explored topic in the literature, no analytical model that can simultaneously deal with these variables is currently available. To bridge this gap, we introduce a queue model for Markovian processes, which enables us to jointly optimise the aforementioned control variables. A discrete-event simulation is then used to validate our model, and we then test our proposal with real data under different operative scenarios, with the aim of assessing the usefulness of the proposal in real settings.
Highlights
Order picking is the retrieval of items in a warehouse to fulfil customer orders and is essential in end-product warehouses for guaranteeing high service levels to customers while aiming to reduce both operational and equipment costs
We focus on the tactical level, where the problem of dimensioning an order picking area involves more control variables, from the size of the forklift fleet to the number of pickers operating within the area. e pickers receive and separate the pallets coming from the warehouse
The user population is infinite and without limit, as is the queue. e arrival rate to the system can be described as λ of a single automated guided vehicles (AGVs) multiplied by the number U of active AGVs, while the service rate of the system is μ of each single picker multiplied by the number of pickers
Summary
Order picking is the retrieval of items in a warehouse to fulfil customer orders and is essential in end-product warehouses for guaranteeing high service levels to customers while aiming to reduce both operational and equipment costs. De Koster, Le-Duc, and Roodbergen [10] provided an extensive review of order picking design and control and focus on studies that address the main problems arising in pickers-to-parts systems and highlight their interactions under a hierarchical decision framework consisting of layout, storage assignment, zoning, batching, and routing. A basic constraint is that the arrival rate of the system is lower than its service rate, which avoids an infinite queue at the regime condition, and the traffic intensity of the system must be less than 100%
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