Every year the world faces many different and diverse types of disasters. The effects of these catastrophes are vast and disastrous for humanity. The most critical stage in the management of disasters is the response phase. The design of an effective emergency response network is important to mitigate the effects of a disaster. The primary mission of any response system is to save the lives of people and rescue civilians, but the emergency systems are working under abnormal operating conditions with an overload of demand and a lack of information. Accordingly, the decisions made to allocate and schedule multiple types of resource units are critical. This dissertation proposes a mathematical model, which applies fuzzy set theory concept, to evaluate the expected demand in the disaster-prone area. This can support decision-makers to allocate and schedule multiple resource type units accurately. Different heuristics introduced will increase the foresight and success of emergency networks and their control of resource systems. Consequently, the response system will be more effective in reducing the number of civilian injuries and fatalities.