Scheduling and Routing with Degradation-Triggered Job Arrivals: An Application to Aerial Forest Firefighting

We address a scheduling and routing problem where new jobs emerge during the operational phase due to the degradation of existing jobs. Specifically, given a set of potential job locations, the demand for an existing job increases over time, and once it exceeds a specific threshold, it triggers the arrival of new jobs at other locations. An unprocessed job at any location progressively reduces the value of the location, and the overall objective is to maximize the total remaining reward across the entire region. The underlying motivation of this problem aligns with the proverb “a stitch in time saves nine.” The problem finds practical application in aerial forest firefighting. In this context, timely intervention in existing fires by aerial vehicles is critical to prevent the spread of fires and to maximize the preservation of value in threatened regions. A comprehensive mathematical optimization model is developed and its performance is validated through computational experiments. The model is then demonstrated across various scenarios in a case study based on California wildfires.
This research is a joint work with Rajan Batta and Esther Jose from the Industrial Engineering Department at the University at Buffalo, US.

Short Bio

Erdi Dasdemir is an Assistant Professor in the Department of Industrial Engineering at Hacettepe University. He obtained his Ph.D. in industrial engineering from Middle East Technical University in 2021. The focus of his Ph.D. thesis was on multi-objective UAV route planning. His doctoral research received support from the Air Force Office of Scientific Research (U.S.), the Council of Higher Education (Turkey), and the Scientific and Technological Research Council of Turkey. In 2019, he served as a visiting Ph.D. student in the Department of Industrial and Systems Engineering at the University at Buffalo, US. Subsequently, in 2022, he rejoined the same department, this time as a visiting faculty member. His research centers around mathematical modeling, multi-objective optimization, and evolutionary algorithms. His work primarily contributes to solving routing problems associated with both manned and unmanned vehicles. He has a profound interest in computer programming, particularly for data science applications. He also actively collaborates with industry partners, addressing their optimization challenges. He teaches data analytics and mathematical modeling courses at both the undergraduate and graduate levels.

Venue

Middle East Technical University
Department of Industrial Engineering Seminar

Friday, April 19, 2024, 4.00 pm
IE Building, Halim Doğrusöz Auditorium (Ground Floor -03)