Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Integrated Simulation-based Optimization of Operational Decisions at Container Terminals

Version 1 : Received: 6 December 2020 / Approved: 8 December 2020 / Online: 8 December 2020 (09:59:50 CET)

A peer-reviewed article of this Preprint also exists.

Kastner, M.; Nellen, N.; Schwientek, A.; Jahn, C. Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals. Algorithms 2021, 14, 42. Kastner, M.; Nellen, N.; Schwientek, A.; Jahn, C. Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals. Algorithms 2021, 14, 42.

Journal reference: Algorithms 2021, 14, 42
DOI: 10.3390/a14020042

Abstract

At container terminals, many cargo handling processes are interconnected and take place in parallel. Within short time windows, many operational decisions need to be taken considering both time and equipment efficiency. During operation, many sources for disturbance exist. These are the reason why perfectly coordinated processes are possibly unraveled. An approach that considers disturbance factors while optimizing a given objective is simulation-based optimization. This study analyses simulation-based optimization as a procedure to simultaneously scale the number of utilized equipment and to adjust the choice and tuning of operational policies. The four meta-heuristics Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search guide the simulation-based optimization process. The results show that simulation-based optimization is suitable to identify the amount of required equipment and well-performing policies. Thereby, there is no clear ranking which of the meta-heuristics finds the best approximation of the optimum. The approximated optima suggest that pooling terminal trucks as well as a yard block assignment close to the quay crane is preferable. With an increasing number of quay cranes, the number of optimal terminal trucks for each quay crane decreases as well as the range of truck utilization within one experiment.

Subject Areas

container terminal; simulation; simulation-based optimisation; meta-heuristic; horizontal transportation

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