An Extended Model for the UAVs-Assisted Multiperiodic Crowd Tracking Problem

The multiperiodic crowd tracking (MPCT) problem is an extension of the periodic (PCT) problem, recently addressed in literature and solved using iterative solver called PCTs solver. For a given crowded event, MPCT consists follow-up crowds, unmanned aerial vehicles (UAVs) during different periods life-cycle open area (OCA). Our main motivation to remedy important limitation “PCTs myopia” which is, certain cases, unable manage fleet UAVs cover all OCA event. behavior crowds can be predicted machine learning techniques. Based on this assumption, we proposed new mixed integer linear programming (MILP) model, MILP-MPCT, solve MPCT. MILP-MPCT was designed technique build two objective functions that minimize total time energy consumed by under set constraints related problem. In order validate simulated it IBM-ILOG-CPLEX optimization framework. Thanks “clairvoyance” experimental investigations show model provides strategic moves between charging stations (CSs) provide better solutions than those reported literature.