This research work aims to describe a Resource Management (RM) approach which was developed in such a generalized way that allows its adaption and implementation in other high-stake sectors. There are a lot of cases that there are strong needs for immediate response and the best possible allocation of resources. The below methodological approach is characterized as a bi-objective dynamical and deterministic. The proposed methodological approach is based on the principles of Dynamical Programming (DP), which discretizes the optimization problems in stages and the techniques of Linear Programming (LP) to identify the optimal transportation plan at every stage utilizing live data from Google. This kind of problem is considered multiplicative because there are two principal objectives: (a) the emergency to transport the injured according to their triage scale and (b) the immediate movement of the patients to the hospitals. Also, the problem can be characterized as multiplicative because of (a) the existence of many start points and destination points of the ambulances with different distances and availabilities, (b) the destination points of one stage become the start points of the next stage, increasing the multiplicity of the problem, and (c) the need to achieve global optimization of the time response in relation to the emergency and priorities of the patients’ condition. The above proposed methodological approach is illustrated through a case study involving the timely transfer of injured people as a result of a natural disaster to the nearest hospitals at a local level.