Decision support tools to assist warehouse managers designing efficient order picking systems

Complex market conditions and new developments make warehouse manager's job hard. E-commerce and globalisation intensify competition among warehouses. The high expectations of customers to provide unique products and quick deliveries force warehouses to increase storage capacity, while at the same time reducing pick times. Additionally, expensive industrial land and high labour costs put pressure on the warehouse costs. To cope with these challenges, a wide range of order picking planning problems need to be optimised. Previous academic research focusses mainly on individual planning problems, without accounting for existing real-life features. Optimizing order picking planning problems sequentially may yield a suboptimal overall warehouse performance. Furthermore, excluding real-life features when developing algorithms and decision support tools prevents managers from using the academic findings in practice. In this talk, I will present appropriate research methods to combine order picking planning problems and account for real-life features (e.g., safety constraints, due time constraints, picker blocking) which support warehouse managers to design efficient manual order picking systems.