For the purpose of analyzing the influence of the recent environmental changes of container logistics system in container terminal, the simulation model of container logistics system on BCTOC is developed in this paper. The simulation model is accomplished by the AweSim simulation language, and the several data which have been used in simulation gained through spot research and basic statistic analysis using the first half of 1998 electronic data in BCTOC. The results of this study are as follows; (1) In the case of BCTOC, the decreasing of container volumes is observed during the first half of 1998 compare with that of 1997. (2) In the container handling service market, the monopolistic market system in the past rapidly diverts to the competition market system from now. (3) From the simulation results, the improving of container logistics system is observed. (4) Because of these results, BCTOC will come to strengthen customer service and competitive power through starting On-Dock service system and operating the team of customer management in the long term.

For the purpose of building the simulation model on cargo handling capacity in container terminal we composed a model of container logistics system which has a 4 subsystem; cargo handling transportation storage and gate complex system. Several data are used in simulation which were gained through a field study and a basic statistic analysis of raw data on BCTOC from January to Jane in 1998. The results of this study are as follows; First average available ratios of each subsystems were 50% for G/C, 57.5% for Y/T, 56% for storage system and 50% for gate complex. And there were no subsystems occurring specific bottleneck. Second comparing the results of simulation to the results of basic statistics analysis we can verifying the suitability of this simulation model. Third comparing the results of this study to the results of existed similar study in 1996, we were able to confirm the changes of container logistics system in BCTOC.

Because of the sharp increase of its export and import container cargo volumes contrast to the lack of related Container Terminal facility, equipment and inefficient procedure, there is now heavy container cargo congestions in Pusan Container Terminal. As a result of such a situation, many container ships avoid their calls into Pusan port. This is a major cause that in tum kads to weakening intemational competitiveness of the Korean industry. This study, therefore, aims are to make a quantitative analysis of Container Terminal System through the computer simulation, especially focusing on its 4 sub-system of a handling system, 'it is checked whether the current operation is being performed effectively through the computer simulation. The overall findings are as folIows; Firstly, average tonnage of the ships visiting the BCTOC was 32,360 G/T in from January '96, to may '96. The average arrival interval and service time of container ships at BCTOC are 5.63 hours and 18.67 hours respectively. Ship's arrival and service pattern at BCTOC was exponential distribution with 95% confidence and Erlang-4 distribution with 99% confidence. Secondly, average waiting time and number of ships was 9.9 hours, 235 ships(38%) among 620 ships. Number of stevedoring container per ship was average 747.7 TED, standard deviation 379.1 TEU and normal distribution with 99% confidence. Thirdly, from the fact that the average storage days of containers at BCTOC are 2.75 days (3.0 days when import, 2.5 days when export). it is founds that most containers were transfered to the off-dock storage areas with the free periods(5 days when import, 4 days when export), the reason for which is considered to be the insufficient storage area at BCTOC. Fourthly, in the case of gate in-out at BCTOC, occupied containers and emptied containers are 89% and 11% respectively in the gate-in, 75% and 25% seperately in the gate-out. Finally, from the quantitative analysis results for container terminal at BCTOC, ship's average wating time of ships was found to be 20.77 hours and berth occupancy rate(σ) was 0.83. 5~6 berths were required in order that the berth occupancy rate(σ) may be maintained up to 60% degree.