A Simulation Optimisation Framework for Container Terminal Layout Design

Lee, Loo Hay; Chew, Ek Peng; Chua, Kee Hui; Sun, Zhuo; Zhen, Lu

doi:10.1007/978-0-85729-652-8_14

Cited by 5 publications

(1 citation statement)

References 16 publications

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“…The core idea of EA-based multi-objective simulation optimization algorithms is to assemble the EA with the simulation budget allocation rule to reduce the negative impact of noise on evaluations. Lee et al [17] coupled the Multi-objective Optimal Computing Budget Allocation (MOCBA) algorithm [18] to the genetic algorithm for a terminal layouts problem. Feng et al [19] integrated MOCBA with a non-dominated sorting genetic algorithm II for the medical resource allocation.…”

Section: B Multi-objective Simulation Optimization For Desmentioning

confidence: 99%

Multi-Fidelity Simulation Modeling for Discrete Event Simulation: An Optimization Perspective

Chen

Hong

Zhang

et al. 2023

IEEE Trans. Automat. Sci. Eng.

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Multi-fidelity simulation is an effective approach to balancing speed and accuracy in expensive simulation, and its performance is affected by the quality of multi-fidelity simulation models. Building high-quality simulation models is nontrivial, especially for complex systems, because current manual modeling methods require sufficient domain knowledge and experience, increasing the labor and time costs. Motivated by the issues, this paper focuses on one of the most crucial simulation types, discrete event simulation, and develops a computer-aid multi-fidelity simulation modeling method called Optimizationbased Multi-fidelity Simulation Modeling (OMFSM). OMFSM formulates multi-fidelity simulation modeling as a bi-objective simulation optimization problem to optimize speed and accuracy. An efficient optimization algorithm called Multi-objective Simulation Optimization based on Hypervolume (MOSO-HV) is tailored to select a set of high-quality models. Experimental results in a digital twin emergency department demonstrate that the computer-aid modeling method builds more and better multi-fidelity simulation models than manual modeling and reveal the effectiveness of MOSO-HV for OMFSM. The utility of OMFSM in multi-fidelity simulation is also justified by a real-world optimization problem. Note to Practitioners-Multi-fidelity simulation is an essentialtechnique to fulfill the demand for accuracy analysis and quick decision-making in Industrial 4.0, such as digital twins and virtual reality. The quality of multi-fidelity simulation models significantly influences the performance of multi-fidelity simulation.

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Section: B Multi-objective Simulation Optimization For Desmentioning

confidence: 99%