INFORMS: What inspired you to research this particular topic?

BAYRAM: There has been a significant increase in the number of natural and man-made disasters over the past decades. The massive amount of destruction caused and the tremendous operational challenges imposed by disasters on governments and humanitarian agencies illustrate the importance of a disaster management program. An important part of such a program is to evacuate a disaster region to protect people threatened by the disaster. The unusual surge in traffic demand far beyond the capacity of the road network and the fact that people’s lives are at stake, make the evacuation traffic management problem critical. Often, the problem of locating safe shelters is solved independently from evacuation traffic management/planning problem, or ignored. Generally, an evacuation traffic management/planning problem is solved with shelter location decisions as given. However, considering these two problems separately may result in suboptimal, i.e., less efficient evacuation plans. Considering these two problems simultaneously renders the problem a hard one. Additionally, the inherent uncertainty in such problems increases the complexity of the problem. As such, saving human lives and the challenges of this problem are my main motivation.

INFORMS: Did any of your results surprise you?

BAYRAM: This work presents an integrated, efficient, and fair strategic evacuation planning tool. It is efficient as to how fast the population at risk is evacuated and it is fair in terms of the distance of safe shelters that evacuees are assigned to and the length of the routes they have to take to reach the shelters. With the methodology proposed in this work, the capability to generate efficient evacuation plans for mass evacuations in real-size road networks considering a large number of scenarios (up to 1,000) representing the uncertainty in evacuation demand, disruption/degradation of road network, and disruption of shelters is attained. The algorithms in the paper can solve such instances of the evacuation problem in moderate times. This we achieve by using second order cone programming duality results in a Benders decomposition setting. I was expecting to see that “considering shelter location decisions simultaneously with shelter/route assignment decisions” and “including the uncertainty” in an evacuation problem would definitely help to have a more efficient evacuation plan. But I must admit that the results were more significant than I expected. Specifically, the location decisions for safe shelters are very critical and drastically affect the efficiency of an evacuation plan.

INFORMS: What is the most important take-away you hope readers will learn from your paper?

BAYRAM: I believe the most important result of this paper is to show the readers that a realistic, efficient, and fair evacuation plan can be achieved by the evacuation planning model and algorithms proposed. Although inclusion of congestion effects, shelter location decisions, and the incorporation of uncertainty represented by a large number of scenarios and using real-size road networks render the evacuation planning problem a very hard one, the algorithms proposed in this paper exactly and efficiently solve the problem in moderate times.

INFORMS: How can the methods used in this paper be applied to what’s currently happening with Hurricanes Harvey and Irma?

BAYRAM: It is sad to see that necessary lessons are not taken after hurricanes such as Katrina and Rita to have better evacuation plans. As the Houston mayor said, “It takes a lot of preparation. You have to have an evacuation plan.” It takes time, effort, and a lot of coordination, but it is doable. In my opinion "evacuation without an evacuation plan" is a bad decision. I believe the methodology used in this paper can be used to prepare an efficient and fair, strategic evacuation plan that could help in mass evacuation of cities due to hurricanes such as Harvey and Irma or other kinds of disasters.

INFORMS: Tell us about the process of writing this paper.

BAYRAM: This paper is a part of the graduate studies I conducted at Bilkent University and during my time as a postdoctoral researcher at the University of Waterloo, which I finalized after starting as an assistant professor at TED University. At the same time, I was working as a researcher in a project supported by the Scientific and Technological Research Council of Turkey [Grant 213M434] and under the supervision of my advisor Professor Hande Yaman—without her continuous support, this work could not achieve the same success. The project was titled “Nonlinear Mixed Integer Programming Models and Algorithms for Evacuation Planning,” and aimed to generate evacuation plans for an impending major earthquake in Istanbul, Turkey, to protect the population from the secondary disasters such as tsunamis, landslides, floods, fires, and aftershocks that are expected to be caused by the initial major earthquake.

INFORMS: Why was it important for you to publish in Transporation Science?

BAYRAM: The success of evacuating a disaster region is based on how well the evacuation traffic is managed. Transportation Science is the leading journal in the area of transportation analysis with a strong emphasis on operational and social concerns. For that reason I believed that Transportation Science would be the best outlet for the paper to be published so as to have a strong influence on the governments and evacuation planning authorities as well as on INFORMS societies and readers.

INFORMS: Tell us a little about what you are working on now.

BAYRAM: I am working on a warehouse management problem using data analytics and optimization techniques. This work is actually part of the research I conducted in a project supported by a supply chain management consultancy company in Canada. We investigated the data collected from a warehouse for descriptive and predictive analytics and developed optimization methodologies (branch and price, robust optimization) for batching decisions to improve the warehouse processing times. I will be presenting this work as “Data-Driven Robust Order Batching for Warehouse Management: A Branch and Price Approach” at the INFORMS Annual Meeting in Houston.

I have another ongoing research titled “Hub Location under Congestion and Capacity Considerations: An Exact Solution Approach.” We developed a path-based formulation for a multiple allocation hub location problem under congestion effect, where hub capacities, assignment of demand to paths and hub(s) are decision variables. We allow a path to have one or more hubs. We develop solution methodologies based on Benders decomposition, second order cone programming, and column generation to solve the problem.

INFORMS: How do you yourself keep up-to-date on the latest research in your field?

BAYRAM: INFORMS PubsOnLine is a perfect venue that serves this purpose. I also try to read related articles, follow the news and updates from related websites, journals and social media, and attend conferences or talks.

INFORMS: What about your career might surprise us?

BAYRAM: I was an officer in the Turkish Army prior to completing my PhD. I have commanded and served in different units and divisions of the Turkish Armed Forces as an Artillery Officer and Operations Research Analyst both in Turkey and abroad, including NATO for almost 20 years, before retiring as a Lieutenant Colonel. Professors Gerald G. Brown and Robert F. Dell, who were my advisors during my master’s at the U.S. Naval Postgraduate School, Department of Operations Research, have always been a real support and a source of motivation in my decision continue my career as an academician.

INFORMS: When you’re not using your OR/MS superpowers to try to make the world a better place, what are some of the ways you like to spend your time?

BAYRAM: I try to spend my time with my family, specifically with my beloved two-year-old daughter Öykü, as much as possible. I enjoy traveling and seeing new places.

INFORMS: What is the best advice you can give to students in your field?

BAYRAM: I tell them to gain knowledge as a practitioner in the field whenever possible as it is very important to combine theory with practice in humanitarian logistics. Knowing how things work in the field will make them stronger researchers.

INFORMS: What are you looking forward to most about attending the INFORMS Annual Meeting in Houston?

BAYRAM: Meeting colleagues from all around the world and getting to know what they are working on as well as sharing my work and getting feedback from them.

INFORMS: What is your least favorite mode of transportation? Can you apply a routing problem to make it better?

BAYRAM: I should say airplanes, not because I do not like flying but because of the issues regarding check-ins and security checks, which can make your life at an airport miserable especially if there is congestion. That’s the reason why I am working on a hub location problem under congestion and capacity considerations.

INFORMS: Which social network do you use most and why?

BAYRAM: I use LinkedIn and Twitter to stay up-to-date in my area and follow the work of my colleagues.