Volunteer Team Formation under Convergence in Post-Disaster Search and Rescue Operations

There have been decades of research in the field of humanitarian logistics, and academics in the field of logistics are becoming more and more interested in it. That being said, we still acquire insight and identify new problems with each disaster. We have also observed various humanitarian logistics applications during Covid-19, e.g. for PCR test sites and vaccination centers. Unfortunately, the recent earthquake in Turkey has led us to re-evaluate the response cycle of disaster management. Close inspection reveals that this response phase actually leads to a variety of new applications of distribution logistics problems. We investigated the potential decision problems and linked these problems with OR literature. During this talk we will explain the general framework and then we will focus on “ Volunteer Team Formation under Convergence in Post-Disaster Search and Rescue Operations”.

In the aftermath of large-scale disasters, the effectiveness of urban search and rescue (USAR) operations depends heavily on the rapid organization and deployment of available human resources. While professional rescue teams are often limited in number, spontaneous volunteers constitute a significant yet highly uncertain source of operational capacity. Coordinating these volunteers efficiently under incomplete information and evolving field conditions remains a major challenge for disaster response planning.

This study proposes an optimization and simulation framework for volunteer-based USAR operations in urban disaster environments. We first develop a mixed-integer programming (MIP) model that forms rescue teams and assigns them to debris sites by considering team–debris compatibility, volunteer proficiencies across operational roles, estimated debris workloads, and team formation requirements. The objective is to maximize feasible early debris coverage while ensuring operational compatibility between rescue teams and debris characteristics. To better represent the realities of disaster response, the optimization model is integrated with a discrete-event simulation framework. The simulation captures uncertain debris workloads, stochastic volunteer arrivals over time, and dynamically changing rescue conditions. The framework also incorporates time-dependent victim survival dynamics, where survival probabilities decrease as delays in first access to debris sites increase. Computational experiments demonstrate how compatibility restrictions and operational constraints significantly influence feasible debris coverage and rescue performance. The proposed framework contributes to humanitarian operations research by integrating team formation, compatibility-based assignment, and dynamic rescue processes. The model provides a realistic and flexible approach for improving volunteer coordination and operational planning in post-disaster search and rescue operations.