An efficient evolutionary solution to the joint order batching - order picking planning problem

This paper introduces an innovative solution to the joint Order Batching - Order Picking Planning Problem. Previous research on this field has mainly focused on solving the two problems separately. Failing to consolidate the two components, however, this approach leads to sub-optimal solutions. In this work we propose a Genetic Algorithm for Joint Optimization (GAJO), which optimizes the integrated problem. Thorough experimentation shows GAJO to be both more effective and faster than the baseline models.