### **README for LOGMS Simulation Dataset**



This readme file was generated on 2026-03-31.



#### GENERAL INFORMATION

Title of Dataset: Performance Metrics and Approximations for Container Terminal Horizontal Transport (LOGMS Data)



Date of data collection: 2025-11-01 - 2026-01-26



Geographic location of data collection: Hamburg, Germany



Institution: MLS, TU Hamburg



Funding sources: Deutsche Forschungsgemeinschaft (DFG)



#### Citing

Please use these information: https://doi.org/10.15480/882.16938

#### DATA \& FILE OVERVIEW

File List: \* LOGMS\_data.csv: The primary dataset containing simulation results and calculated performance indicators for various container terminal scenarios.



Relationship between files: This dataset builds upon previous simulations by introducing specific allocation strategies ("Fixed" vs. "Combined") and detailed wait-time analysis for both cranes and trucks. You can find our previous Simulation data here:  https://doi.org/10.15480/882.16722



#### METHODOLOGICAL INFORMATION

Description of methods used for data generation: The data was generated using a discrete-event simulation of container terminal operations. The model focuses on the interaction between Quay Cranes (QC) and Terminal Trucks (TT). Tecnomatix Plant Simulation by Siemens was used.



#### Key Experimental Variables:



Allocation Strategies: "Fest" (Fixed assignment of trucks to cranes) and "Kombi" (Combined/Shared pool of trucks).

For more Information regarding these strategies have a look at our related puplication Assignment of Orders in Horizontal Transport at Sea-port Container Terminals at LOGMS 2026.



Availability: Variations in TT\_Availability and QC\_Availability (representing technical reliability).



Speeds: Variations in travel and handling speeds.



Processing/Calculation: The simulation results (Productivity, Waitingtime) are compared against analytical models (PRO\_m (fixed) and PRO\_m (shared)) to calculate the relative deviation (rel Dev PRO\_m).



#### DATA-SPECIFIC INFORMATION FOR: LOGMS\_data.csv

Number of variables: 48



Number of rows: 161



#### Variable List \& Definitions:

1\. Configuration Parameters

Name / Experiment: Unique identifier for the simulation run (e.g., Fest\_8TT\_A\_D\_I\_L).



t\_CB / t\_TT: Mean handling/cycle times for Cranes and Terminal Trucks \[seconds].



std\_CB / std\_TT: Standard deviation of handling times.



Allocation: Strategy used (Fest = Fixed, Kombi = Combined).



Number of TTs / QCs: Quantity of active Terminal Trucks and Quay Cranes.



TT\_Speed / QC\_Speed: Speed parameters for the equipment.



TT\_Availability / QC\_Availability: Percentage of time the equipment is operational (0.0 to 1.0).



2\. Performance Metrics (Simulation Results)

Productivity\_QC (Mean/Std): Actual throughput per Quay Crane \[units/hour].



Max\_Productivity\_QC: Theoretical maximum throughput.



Handlingtime\_QC (Mean): Pure processing time at the crane.



Waitingtime\_QC / Waitingtime\_TT: Average time equipment spent waiting for a counterpart.



Vessel\_handlingtime: Total time required to process the vessel in the simulation.



3\. System State \& WIP

WIPO\_process: Work-in-process currently being handled \[units].



WIPO\_queue: Work-in-process waiting in queues \[units].



WIPO\_ges: Total Work-in-process in the System \[units].



4\. Analytical Comparison (Approximation)

U\_m (fixed/shared): Calculated utilization based on analytical formulas.



PRO\_m (fixed/shared): Approximated production rate.



Dev PRO\_m / rel Dev PRO\_m: Absolute and relative deviation between simulation (Productivity\_QC) and the analytical model.