## 7 Conclusions  
Organizational decisions after MCI's occurrence are made on the basis of intuition and experience of rescue DES functionaries; the flow of information between individual rescue functionalities is still largely limited to voice transmission via radio communication. The DES continues to prepare for the MCI using traditional methods such as color-coded triage paper cards. The results of simulation studies conducted with the developed CSMRO indicate that DES decision-making processes in MCIs can be significantly improved. The CSMRO can be used for the optimal allocation of available DES forces and resources to those injured in the MCI. This translates strictly into a maximum reduction in time for the injured to reach designated HEDs. The time for the CSMRO to work out a decision on how to handle a mass event has been significantly reduced to less than a second (depending strictly on the computing power of the computer). As a result, the execution time of the actions taken in various stages of the rescue operation will also be shorter. Computations made in the developed CSMRO simulator clearly indicate that the implementation of the developed Intelligent Medical Rescue Operations Management System will:  
* significantly shorten the time of decision-making in mass casualty incident handling,
* improve the accuracy of decisions regarding medical care of the injured,
* reduce the stress factor in DES physicians by supporting the decisions made,
* maximize the use of DES forces and resources available at a given moment and
* eliminate information chaos and minimize the risk of making a mistake. The proposed simulator was developed in close cooperation with the Polish Emergency Services. It presents the specifics of mass casualty incidents management in Poland, \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Literature** & **Optimization** & **Is Multi-Criteria** & \begin{tabular}{c} **New Method of** \\ **Triage or** \\ **Currently in** \\ **Practice START** \\ \end{tabular} & \begin{tabular}{c} **Injured Persons** \\ **Health Modelling** \\ \end{tabular} & \
\begin{tabular}{c} **Complete Service** \\ **(injured Assigned** \\ **to the Certain** \\ **MRT and ED)** \\ \end{tabular} \\ \hline
\begin{tabular}{c} [PERSON] et al. [4] \\ \end{tabular} & Discrete-event simulation & no & START & no & yes \\ [PERSON] [13] & Hyperheuristic & no & START & no & no \\ [PERSON] et al. [14] & D’Hond, greedy strategy & no & START & no & yes \\  & simulated annealing & no & START & no & yes \\  & Fixed Job Scheduling Problem & & & & \\  & Variable Neighborhood Search & & & & \\ [PERSON] et al. [17] & (VNS) metaheuristics and its & yes & START & no & yes \\  & deterministic variant Variable & & & & \\  & Neighborhood Descent (VND) & & & & \\ [PERSON] and [PERSON] [11] & MIP & no & START & no & yes \\  & Pontryagin’s minimum & no & START & no & yes \\  & principle & no & START & no & yes \\  & MIP & & & & \\ [PERSON] et al. [20] & Flexible job shop scheduling & no & START & no & yes \\  & model and a genetic algorithm & & & & \\ [PERSON] et al. [26] & MIP & no & START & no & yes \\ [PERSON] and [PERSON] [27] & LP, column generation & no & START & no & yes \\  & Rapid-screening algorithm and & & & & \\ [PERSON] et al. [37] & an adaptive particle global and & no & START & no & yes \\  & hyperbox local search & & & & \\ \hline
**The proposed model** & **MIP** & **yes** & **new** & **yes** & **yes** \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Comparison of the proposed model with selected models found in the literature. is adapted to local realities, and is already planned for implementation in mass casualty incidents management teams in the near future. The main limitation of the CSMRO approach is shifting from typical telecommunications to a data exchange system. The communication infrastructure needed to ensure communication of the IMROMS system modules needs to be established. Another issue is to equip the DES with hardware infrastructure, servers, mobile devices, etc.