Solution approaches for the integrated order picking problem in multi-depot warehouse layouts

One of the most dramatic changes in real world business environment is to have new direction from traditional commerce to e-commerce environment. This change has many reasons but one of the most significant and accelerator reason is the Covid-19 global pandemic period. Throughout this pandemic period, people have procured everything they might need through e-commerce companies over the Internet. As a result of this alteration, managing order picking operations effectively and efficiently in companies has become much more substantial. The primary contribution of this thesis is to handle multiple input/output (I/O) points (i.e., depots) and multiple pickers in a holistic approach for integrated order picking problem for the first time. To handle the mentioned problem from the static viewpoint, firstly, a new Mixed-Integer Linear Programming (MILP) model is developed. Secondly, a novel variant of Harmony Search Algorithm is improved to find near optimal solution for large-sized problems in reasonable time and it is called "Dependent Harmony Search (DHS) Algorithm". Thirdly, Agent-Based Modeling and Simulation (ABMS) approach is used to address the problem from a dynamic perspective. As a conclusion, this thesis proposes a new warehouse layout with multiple depots and multiple pickers and develops solution approaches to solve order batching and assignment problems in both static and dynamic perspectives.