  The multi-Agent Pickup and Delivery (MAPD) problem is crucial in the realm of
Intelligent Storage Systems (ISSs), where multiple robots are assigned with
time-varying, heterogeneous, and potentially uncertain tasks. When it comes to
Human-Swarm Hybrid System ((HS)$_2$), robots and human workers will accomplish
the MAPD tasks in collaboration. Herein, we propose a Human-Swarm Hybrid System
Pickup and Delivery ((HS)$_2$PD) framework, which is predominant in future
ISSs. A two-layer decision framework based on the prediction horizon window is
established in light of the unpredictability of human behavior and the dynamic
changes of tasks. The first layer is a two-level programming problem to solve
the problems of mode assignment and TA. The second layer is devoted to the
exact path of each agent via solving mixed-integer programming (MIP) problems.
An integrated algorithm for the (HS)$_2$PD problem is summarized. The
practicality and validity of the above algorithm are illustrated via a
numerical simulation example towards (HS)$_2$PD tasks.
