A Multi-Attribute Decision Support System for Allocation of Humanitarian Cluster Resources Based on Decision Makers’ Perspective

The rush of the humanitarian suppliers into disaster area proved to be counter-productive. To reduce this proliferation problem, present research is designed provide a technique for supplier ranking/selection in response using principles utility theory. A resource allocation problem solved optimisation based on decision maker’s preferences. Due lack real-time data first 72 h after strike, Decision Support System (DSS) framework called EDIS introduced employ secondary historical from four clusters (WASH: Water, Sanitation and Hygiene, Nutrition, Health, Shelter) estimate demand affected population. methodology multi-attribute decision-making (MADM), Analytical Hierarchy processing (AHP) Multi-attribute theory (MAUT) provides following results. First need estimation put forward minimum standard requirements response. Second, method optimization partners selection provided resources they have available during phase. Third, an preferences makers. This does not require aftermath disasters estimation, partner before MIRA report released.