Dr. Rajan Batta will hold a two-part workshop on using UAVs to search for targets (entities) in disaster areas.
WORKSHOP
Using Operations Research Methods to Guide UAV Search in a Disaster Area
Dr. Rajan Batta, SUNY Distinguished Professor, Department of Industrial and Systems Engineering, University at Buffalo, USA
The first part of the workshop focuses on search path optimization for recording emerging targets. This portion of the work considers the situation where targets emerge according to a non-homogeneous space-time Poisson process during the mission. The only provided information is the time-dependent arrival rate function for each cell in the area. Two heuristics are proposed. The first heuristic is based on an approximation of the target recording problem as an orienteering problem with time windows (OPTW), in which the time window settings for each cell are associated with the type of target-emerging condition that it represents. These second heuristic is based on a tabu search method. To analyze the effectiveness of both heuristics, target arrivals are simulated across a suitable number of replications and summary statistics are obtained. Further, computational testing is conducted to study the impacts of three factors: sensor-capture radius, UAV speed, and UAV service time. The factorial analysis shows that sensor-capture radius and UAV service time affect performance significantly. Both heuristics deliver comparable solutions, with the tabu search method consuming less CPU time. In terms of managerial insights, what we find is that cell visitation priorities should be based on a combination of factors that includes its target-emerging conditions, distance from the start and endpoints, and available mission time.
The second part of the workshop focuses on a situation where sub-regions with targets present have already been identified. The goal is to develop a search and route plan for the UAV so as to maximize the total number of targets detected within a limited mission duration. First, a non-linear Mixed Integer Programming (MIP) model is applied to address the problem. To linearize the model, continuous search time variable is discretized such that it can only take a finite number of possible values. Therefore, the resulting Mixed Integer Linear Programming (MILP) models an approximation of the original problem. Next, an exact solution approach is presented and a clustering heuristic is suggested to solve larger problem instances. To validate the proposed solution methods, extensive computational experiments are conducted. Furthermore, a real-world case study is presented within the humanitarian domain to demonstrate the effectiveness and relevance of the suggested approaches
Dr. Rajan Batta is a SUNY Distinguished Professor in the Department of Industrial and Systems Engineering at the University at Buffalo, USA. He works on search and reconnaissance problems. He also works on supply chain design problems, both in the contexts of humanitarian logistics and manufacturing systems. He is a Fellow of the Institute of Industrial and Systems Engineers (IISE) and the Institute for Operations Research and the Management Sciences (INFORMS). He has been the recipient of several research awards. He has received IISE’s highest award, the Frank and Lillian Gilbreth Industrial Engineering Award. He has also received the Koopman Prize from INFORMS’ Military and Security Society. Another recent award from INFORMS is the Lifetime Achievement Award in Location Analysis.
