Containerized sea-freight transportation has grown significantly these recent year, brought an increasing interest on the optimization on container terminal operations. Recent research trends nowadays leads to the integration of container terminal planning. As the container terminal operations itself consists of some intertwined systems, so the integration between them becomes critical.

Operational efficiency and productivity become the key issues in the development of container terminal operations management. As the service provider, container terminals are expected to satisfy the shipping lines schedule related to the vessel arrival and departure time. In other hand, container terminals are also in the urge of maintaining their operational cost in order to compete with other terminal. Somehow at the container terminal, efficiency and productivity will depend a lot on the operational planning held by the terminal manager.

In the daily practice, terminal managers determine the berthing position of each vessel before they arrived at the terminal, due to the information given by the shipping line and also plotted the handling time for the vessel’s operation. This usually called as tactical berth allocation problem. Then, they also determine the certain position for each container in the yard storage area according to some rules adapted in the terminal, this case called tactical yard allocation problem. In order to attain a good state of container terminal operational planning at tactical level, terminal operators are faced with the challenge to both minimize the total violation time of vessel’s arrival and departure time, and minimize the yard transportation distance in a balanced way.

As one of the Indonesian highest-throughput container terminal, PT. Port of Tanjung Priok is experiencing the throughput escalation, particularly from 2015 to 2016, and confront those tactical problems on berth and yard allocation on their daily practice. Unfortunately, they still encounter the violation of vessel arrival and departure time, which undermining the shipping line schedule. This might happening as the result from the possibility of poor operational planning at tactical level and the lack of integration between berth and yard allocation planning.

To cope with this issue, we are trying to get an optimal model for integrated operational planning for ocean going terminal at PT. Port of Tanjung Priok, by adopting a mixed-integer programming model proposed by (Liu et al. 2016). We are developing the model with the consideration of the actual condition on the terminal as the parameter in order to generate a reliable output. The actual information provided by the terminal manager that counts into the consideration of the model are:

1. Vessel arrival order, vessel length, and number of containers loaded into and discharged from the vessel;
2. Total length and characteristic of terminal’s quay;
3. Number of equipment (quay cranes) available in the terminal;
4. Technical constraints determined by the terminal manager;
5. Layout and capacity of terminal yard storage area.

Some integer variables are set as the major output, assisted with some other minor variables as the supporting of integration process. As well as the parameter, some constraints also generated based on the actual condition of the terminal. The model then solved with a bi-objective optimization method called ɛ-constraint method, thus we set two objective function which are i) minimize the total violation of actual and scheduled vessel arrival & departure time; and ii) minimize the total yard transportation distance representing the terminal’s operational cost.

In the daily practice of PT. Port of Tanjung Priok within the planning horizon of one week, noted that the current condition conform the small class according to generation by (Liu et al. 2016). Since the class is small-scale, it is possible to get an exact global optimum result from the model. Model will generate the optimal number of the two objective functions and the solution set of major variables generated by the model, which are:

• the berthing position of each vessel in the planning horizon along the quayside of terminal;
• number and scenario of equipment will be used at each vessel operation;
• start and end time of vessel operation, representing the arrival and departure time;
• storage position of each container in the yard area.

Then as the final result, we transformed the output into the berth and yard allocation map separately, for the ease of the practical use of the terminal. As the model solved with a bi-objective optimization method, output of the model includes the Pareto Frontier that represents the relation between the two objectives function. It resulted that total violation time has a contrast relation with the total yard transportation distance.

Since the model is considering the actual condition of the terminal, the result has high possibility to be applied in the actual practice at PT. Port of Tanjung Priok. Along with that, the Pareto Frontier could be used as decision support tool to determine the set of scenario that suit the terminal’s particular condition, related to the time violation and yard transportation distance. But, regarding to some sort of limitations within the development of the model, this projects is still needs further improvements in order to get more reliable result.

This research is conducted by Rizka and Komarudin