<p>Effective volunteer management requires ensuring operational continuity and maximizing benefits from all team members. Prioritizing volunteers with adequate knowledge and experience in task assignments is crucial for maintaining workflow continuity. This study employs a two-stage model for allocating areas and tasks to volunteers in search and rescue operations. The first stage identifies the optimal number of volunteer response centers using the P-median problem. Considering population density as demand, 7 out of 14 accessible and protected disaster collection areas meeting basic needs are selected as optimal response centers based on distance. In the second stage, a mixed-integer programming model is proposed for volunteer assignment, which prioritizes assigning the most knowledgeable and experienced volunteers to critical positions. The model’s flexibility and applicability are demonstrated by incorporating voluntary rest periods, which are allocated based on the urgent needs of response centers in various post-disaster scenarios. Solved using GAMS/CPLEX, the model’s results show that expert volunteers in low-demand scenarios are prioritized, working 5 out of 9 shifts, while other volunteers receive insufficient assignments. In high-demand scenarios, some response centers face volunteer shortages, with a deficit of 62 volunteers across 9 shifts in non-emergency areas. The study evaluates the benefits and drawbacks of the volunteer assignment model and offers recommendations for future research.</p>

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A two-stage volunteer assignment model for post-disaster search and rescue operations

  • Umit Ozdemir,
  • Suleyman Mete,
  • Muhammet Gul

摘要

Effective volunteer management requires ensuring operational continuity and maximizing benefits from all team members. Prioritizing volunteers with adequate knowledge and experience in task assignments is crucial for maintaining workflow continuity. This study employs a two-stage model for allocating areas and tasks to volunteers in search and rescue operations. The first stage identifies the optimal number of volunteer response centers using the P-median problem. Considering population density as demand, 7 out of 14 accessible and protected disaster collection areas meeting basic needs are selected as optimal response centers based on distance. In the second stage, a mixed-integer programming model is proposed for volunteer assignment, which prioritizes assigning the most knowledgeable and experienced volunteers to critical positions. The model’s flexibility and applicability are demonstrated by incorporating voluntary rest periods, which are allocated based on the urgent needs of response centers in various post-disaster scenarios. Solved using GAMS/CPLEX, the model’s results show that expert volunteers in low-demand scenarios are prioritized, working 5 out of 9 shifts, while other volunteers receive insufficient assignments. In high-demand scenarios, some response centers face volunteer shortages, with a deficit of 62 volunteers across 9 shifts in non-emergency areas. The study evaluates the benefits and drawbacks of the volunteer assignment model and offers recommendations for future research.