Title: Simulation-Based Optimization for Dynamic Patrol Deployment Planning
Presenter: Yasaman Ghasemi
Date: Monday, April 19, 2021
Time: 1:15 pm – 2:15 pm
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Abstract: Police operations play a crucial role in public safety and the sustainable development of communities. Although police agencies have made decades of effort to improve patrol operations, the policing system’s complex nature often makes it very challenging to manage and control. Specifically, the dynamic and stochastic criminal behavior, the constrained policing resources, and the reactive patrol operations hinder the law enforcement agencies from successfully adopting predictive policing and better understanding the system dynamics, assessing the operational performance, and improving the quality outcome. In this study, a computerized simulation-optimization framework is developed to address the dynamically changing complexities and uncertainties in police operations and adaptively optimizing operational performance based on the state of the policing system. Therefore, an agent-based model (ABM) is developed, with an integration of the Geographic Information System (GIS), to simulate and visualize the underlying patrolling system’s dynamics at a micro-level. The ABM is implemented in AnyLogic, a Java-based multi-simulation platform, based on a set of pre-specified attributes and behavior rules. Moreover, a design of experiments approach is implemented on the ABM to inspect how police actions affect the operational outcomes under a set of system constraints. A real-world case study is presented to illustrate how this framework provides a guideline for dynamic patrol deployment planning. This case study is conducted for the Arlington Police Department (APD), Texas, to verify this concept and enable deployment decisions towards a more effective police patrol operation and dynamically respond to various crime circumstances.
Bio: Yasaman Ghasemi is a Ph.D. Candidate in Industrial Engineering at the Department of Industrial, Manufacturing and Systems Engineering at UTA. She received her B.Sc. degree in Computer Engineering from Azad University and her M.Sc. degree in Industrial Engineering and Management from Linkoping University (LIU), Sweden. Yasaman’s research focuses on Complex Systems Modeling & Optimization, primarily in Healthcare Systems (infectious disease modeling, policy development, and health data analytics) and Policing Systems (dynamic policing decision analytics). One of her promising research projects developed an Agent-Based Simulation Model to investigate the transmission dynamics of infectious diseases in university campuses, aiming to help public health decision-makers quickly respond to the epidemic/pandemic with effective interventions. Her research received a grant through the Research Enhancement Program at UTA.