With the rise of e-commerce, logistics providers are facing increasing retail orders and short delivery deadlines. The Zone Picking Method (RZOP) is particularly suitable for handling such orders. It involves a semi-automated process where a conveyor is used for transportation, and an operator in each zone collects the products.

Organizational issues may arise in an RZOP system, such as unproductive times (operators waiting between bins arrivals) or flow blockages, resulting in costs and delays. The system's performance relies heavily on flow management. The RZOP system is also subject to uncertainties due to variability of the order pickers preparation times and cells obstructions causing conveyor stoppage.

In this thesis, we model, in a deterministic context, a scheduling problem that integrates the system's specific characteristics: bins may not pass through all zones, limited stocks, and transportation between zones. Two mathematical models are developed: a generic version that includes all possible system configurations, and a specific version for configurations where the order of picking stations is given. The objective is to minimize the order pickers cumulative presence time at their stations. Additionally, a discrete event simulation model is developed to study the system's behavior while considering two sources of uncertainty: bins preparation times and conveyor cell blockages. The sequential approach of optimization and simulation is applied to an industrial case study.

Keywords : Retail order picking systems, Zone picking, Scheduling, Optimization, Simulation, Uncertainty.