Agent-Based Modeling (ABM) is an effective strategy for simulating the emergent properties of complex systems. This form of simulation models the behaviors of individual agents interacting with each other and with their world and can be used to predict the outcome of discrete events, such as the behavior of a warehouse. Many frameworks exist for creating ABMs—one such program, used here, is called AnyLogic. While ABM works well for modeling individual behaviors to determine the resulting emergent group properties, it is difficult to find optimal warehouse layouts, configurations, and personnel allocation that allow the warehouse to function as efficiently as possible. Parameters must be tuned and tested to find optimal settings. Unfortunately, the simulation time required to test all possible parameter combinations is prohibitive, making this approach impractical. In this case, it is advantageous to use a highly efficient optimization tool such as HEEDS MDO. While most applications of HEEDS focus on design of physical parts and products, HEEDS can also be applied to many other forms of optimization. This paper discusses the success of HEEDS in the area of optimizing warehouse efficiency, using the agent-based modeling tool AnyLogic.
Download (PDF, 590 KB)