## 4 Concluding Remarks  
The mobile harbor's reliable marine crane technology and container transport using RORO on land berths can be an alternative to handling large container ships. Existing port simulation and analytic methodology is limited in terms of the application to mobile harbors. In this study, we developed a simulation for mobile harbors. Mobile harbor operation logic was developed through cooperation with operators of mid-stream operations and the MH operation logic has a similar operating concept to mobile harbors and a port operation system IT company. Through simulation, various types of scenarios and mobile harbor types can be evaluated flexibly. We proposed a methodology to derive the minimal cost for a mobile harbor design that satisfies a given required service level by utilizing system characteristics. Varying the number of mobile harbors and land berths iteratively derives the optimal number of resources. The port of Surabaya needs a large investment to handle large ships. The port needs to extend and dredge the 40 km channel from the open sea and a new berth needs to be constructed to meet the depth of the water. The use of a mobile harbor will replace these cost investments. Thus, in this study, we proposed a mobile harbor design suitable for Surabaya port by using simulation and a suitable methodology. We generated an optimal design that guarantees the appropriate level of service for four types of mobile harbors. MH is able to reduce 20.8-26.4 M USD/year for the Surabaya port. Our work can be extended in several directions. In [35; 36], it is stated that fuel consumption and emissions can be minimized by effectively maximizing berth productivity and reducing total service time and delayed departures. It is predicted that increasing container throughput by MHs can reduce \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Design** & **\# of MHs** & **\# of Berths** & **Total Cost (M USD/year)** \\ \hline
1 & 36 & 3 & 159.7 \\
2 & 39 & 6 & 161.8 \\
3 & 14 & 2 & 163 \\
4 & 15 & 3 & 165.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Result of the simulation model. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ship Size** & \begin{tabular}{c} **Average IAT** \\ **(Hours)** \\ \end{tabular} & **IAT Pattern** & **Cargo Pattern** & \
\begin{tabular}{c} **\# of Docking Points** \\ **(250 TEU)** \\ \end{tabular} &
\begin{tabular}{c} **\# of Docking Points** \\ **(1200 TEU)** \\ \end{tabular} \\ \hline
1000-2499 & 8.11 & exp (8.11) & uniform (1350;1450) & 2 & 1 \\
2500-3999 & 14.87 & exp (14.87) & uniform (600;700) & 3 & 2 \\
4000-5999 & 59.59 & uniform (54.59,64.59) & uniform (450;550) & 3 & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Input data for detailed simulations. the service time of a containership so that it could reduce the pollution as well, but further research is required to determine if this is really feasible. Designing MH systems to minimize pollution can be a subject for future research. It would be interesting to compare the pollution from traditional harbor systems with that of mobile harbor systems. Also, we could apply this methodology to other intermodal transportation problems, such as those involving airplanes, trains, and trucks. A more detailed control algorithm for the mobile harbor could be developed instead of the FCFS that is used in the simulations. In addition, it would be interesting to study the general architecture and capacity planning problems to identify a unified framework into which all the problems will fit. Such a framework could be generalized to allow for a broader class of problems. [PERSON] designed the simulation of the proposed work and prepared the draft of the paper. [PERSON]-s.K. designed the formulation of the overall work and contributed to the writing of the paper. This research was funded by Korean Ministry of Knowledge Economy Grants 10036222 and 10036229. The work reported here has been supported in part by the Korean Ministry of Knowledge Economy Grants 10036222 and 10036229.