Alocação otimizada de voluntários em cenários de crises integrada ao sistema Contask.

Abstract

This work addresses the challenge of volunteer allocation in crisis scenarios, such as natural disasters, which demand agile, efficient, and adaptable management systems. To tackle this problem, a task allocation engine was developed and integrated into Contask, a prototype system designed for context-aware task distribution. The allocation engine is based on Integer Linear Programming (ILP), combined with heuristics, with the goal of optimizing the distribution of microtasks in an efficient and context-sensitive manner. The proposal considers multiple criteria including availability, skills, location, and task priority drawing inspiration from existing microtasking models. The choice of combining ILP with heuristics was grounded in a systematic literature review, along with a comparative analysis and an evaluation of the model’s applicability to the proposed scenario. This process revealed that alternative approaches present practical limitations related to solution stability and computational cost, especially in emergency contexts where rapid and robust responses are required. The requirements elicitation was conducted through an exploratory study with 15 participants, including experienced volunteers and managers of social initiatives, using questionnaires and thematic analysis to identify key challenges and expected functionalities. Based on these requirements, Contask was redesigned with the implementation of the allocation engine, resulting in an updated prototype of the solution. This prototype was initially evaluated through usability tests and a focus group with six managers, including members of the Mãos que Ajudam project. Subsequently, controlled simulations representing critical situations were performed to further assess system performance. The results indicate strong acceptance of the tool and a preference for automatic allocation, suggesting potential practical applicability and meaningful contributions to intelligent volunteer management in emergency situations.