Multi-objective solution approaches for disaster response operations

İstenç Tarhan,

Lip6, Sorbonne University, Paris, France

Heudiasyc, UTC, Compiègne, France

Abstract

In this talk, we present multi-objective solution approaches developed under the scope of the RESPOND-OR project. The strategic vision of the RESPOND project is to develop solution algorithms to underpin the decision support system for disaster preparedness and response in Indonesia and Sudan. Disaster response personnel routing and scheduling (PRS) and relief supply distribution (RSD) are two of the problems addressed within the RESPOND-OR project. In the PRS problem, disaster response personnel (e.g., evacuation or medical teams) are deployed in the aftermath of the disaster and travel between affected zones to serve them until their demands are fully satisfied. The RSD problem, on the other hand, considers the distribution of the relief supplies positioned at central warehouses down to affected zones through intermediate locations. Both problems aim to optimize efficiency, equity and efficacy of the corresponding operations. For the PRS problem, both exact (a two-stage lexicographic approach) and heuristic (an adaptation of the exact quadrant shrinking method) algorithms are developed. For the RSD problem, we model a time-expanded network based on which an adaptive large neighborhood search is developed. The algorithms developed are tested on a case study using the historical data from the 2018 Lombok Earthquake.

This is a joint work with Konstantinos G. Zografos, Juliana Sutanto, Ahmed Kheiri and Heru Suhartanto.

Short Bio

İstenç Tarhan is a research associate at Sorbonne and Technology of Compiègne Universities. He is also a visiting researcher at Lancaster University CENTRAL Research Center. He received his BS and MS degrees from the Industrial Engineering Department of METU. He completed his PhD in Industrial Engineering and Operations Management Department at Koç University. Prior to his current positions, he was a research associate at Lancaster University Management School. His research interests include the development of mathematical models, heuristic and exact approaches for single and multi-objective combinatorial optimization, particularly scheduling, routing and transportation problems. His studies cover both the empirical and theoretical complexity analysis of the developed algorithms.

Venue

Friday, April 7, 2023, 4.00 pm - Zoom

English

Announcement Category