||Business-to-consumer (B2C) e-commerce sales are booming. To
meet customer expectations at low cost, excellent logistics
performance is indispensable. In this respect, efficiently organizing
order picking operations (i.e. retrieval of items in the warehouse to
fulfil customer orders) is essential.
Unfortunately, current academic literature is lacking models and
algorithms to adequately support order picking decisions in complex,
real-life settings. Therefore, this project will design efficient order
picking planning algorithms that take into account the real-life
characteristics of modern B2C e-commerce warehouse
environments, such as scattered storage, the availability of products,
and picker blocking, all features that are hardly explored
First, new algorithms for integrated order batching and picker routing
under a scattered storage policy are developed, taking into account
product availability. Second, these algorithms are evaluated using a
simulation framework which accounts for picker blocking effects. The
gained insights will be used to enhance the developed algorithms.
Third, the impact of different warehouse configurations and scattered
storage assignments is analysed.
To conclude, we will provide innovative algorithms for complex
optimization problems faced by many companies. As such, the
project goes well beyond the current academic state-of-the-art, and
creates innovative new tools and insights for our current and future ecommerce