# Resource Capacity Requirement for Multi-Terminal Cooperation in Container Ports
## 3 Simulation Experiment  
A set of simulation experiment is conducted to understand the capacity requirements for different volumes of trans-shipment ratios of containers relative to inbound and outbound containers at a terminal, as well as different transferring container volumes across terminals. The base-case setting is as follows: four equal-size of terminals located at a trans-shipment hub port are sharing the resources. Each terminal has 1000 m quasip length and initial inventory at the yard is 20,000 TEUs. The distance between adjacent terminals is set to 500 m, and the terminals are sequentially laid in a line. The truck free speed in between terminal is set to 14 m/s. The traffic density at maximum flow (\(k_{0}\)) in the Underwood formula is calculated by setting the effective speed under jammed traffic (\(u_{N_{max}}\)) to 0.01 m/s, where the maximum number of trucks (\(N_{max}\)) for transferring activities between terminals is limited to 25. The gate service time is preset to follow \(U(5,\ 10)\) min. This service time measures the duration-of-stay of a truck in the boundary of gate system and includes the time spent on checking the driver identification, truck number, container number, and measuring the weight, temperature (for reef), and size (for out-of-gauge) of the container and deciding a storage slot for the container. Additionally, when the container door is not facing outward, a reach stacker needs to turn the direction of the container.  
To avoid the situation whereby insufficient resource capacity leads to a distortion in the actual capacity requirement reflected in the resource profile, the study assumed that the requested QC intensity of every vessel can be met. The QC intensity is determined by the vessel category (size) and the TEU quantity on the vessel described in Appendix A. The vessel and TEU categories in the experiment is drawn upon their respective pools based on a uniform distribution. The gross productivity of a QC is assumed to be normally distributed, \(N\left(28,\ 4^{2}\right)\), hourly. \(t_{open}\) and \(t_{close}\) are set to 2 weeks and 1 day, respectively, and the vessel arrival \(T_{arrival}\) is set to follows exponential interarrival time with a mean of 2.05 hourly. \(t_{unload}\) is set to 2 h after the vessel arrival. It is further assumed that the incoming vessels arrive at any terminal with equal probabilities. The probability that an arriving vessel is a mainline vessel is 90%, while the probability of receiving a feeder vessel is 10%. When the latter occurs, half of these vessels are for unloading and the other half for loading only (note: this contrasts with the mainline vessel which will first perform the unloading operations and then the loading operations). The terminals have equal probabilities to be selected when transferring the trans-shipment TEUs to them.  
The simulation scenarios are represented by varying the rates of transshipment and outbound and inbound TEUs, as well as the rates for which the trans-shipment TEUs would remain in its arrival terminal or be transferred to other terminals. The simulation runs 10 replications for each setting for 200 days after the warming-up period. Since the warming-up period depends on experiment settings, the simulation results are sampled out after eliminating the initialization bias by shown in the output plots. The simulation model is implemented using C# programming language as part of the Visual Studio Community 2017 and run on a computer with Intel processor i5, 1.8 GHz with 16 GB RAM.