AFET GÖNÜLLÜSÜ ATAMA VE YÖNETİM SİSTEMİNİN GELİŞTİRİLMESİ: “BEN DE VARIM TÜRKİYE” MODEL ÖNERİSİ

Disasters, depending on their scale, cause escalating losses of life and property, straining response capacities and rendering professional teams insufficient. This situation makes the effective management of volunteer human resources a critical necessity, particularly during the "golden hours." This thesis presents the "Ben de Varım Türkiye" model, developed to minimize the assignment and management challenges of volunteers who operate either spontaneously or under an institution in disaster areas. The primary objective is to establish a dynamic optimization system that assigns registered and spontaneous volunteers to the "right location" and "right task" based on their competencies, location, and availability. Expert opinions were first obtained from stakeholder groups using the Delphi method to identify management constraints and required competencies. The 12 identified core competency criteria were weighted using the Fermatean Fuzzy DEMATEL method, which models uncertainty over a broader range than classical fuzzy logic. Volunteers were then prioritized according to these criteria using the Fermatean Fuzzy TOPSIS algorithm. The operational robustness of the model was tested on a synthetic pool of 150,000 data points through Monte Carlo simulations (N=10,000 iterations) and Markov Decision Processes. Simulation results demonstrated that the system identifies local resource bottlenecks within seconds, allocates external resources according to the TAMP protocol, and successfully manages chaotic processes. Additionally, the model provides a proactive ecosystem that enhances pre-disaster social resilience through gamification and training modules. By accounting for "stress deviation" during crises, this study proposes a merit-oriented disaster management paradigm that differs from traditional static assignment methods.