scholarly journals Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 42
Author(s):  
Marvin Kastner ◽  
Nicole Nellen ◽  
Anne Schwientek ◽  
Carlos Jahn
Keyword(s):  
Random Search ◽  
Time Windows ◽  
Container Terminals ◽  
Bayesian Optimization ◽  
Solution Quality ◽  
Operational Decisions ◽  
Cargo Handling ◽  
Simulation Based ◽  
Operational Policies ◽  
Simulation Based Optimization

At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics—Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search—guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable.

scholarly journals Integrated Simulation-based Optimization of Operational Decisions at Container Terminals

2020 ◽  
Author(s):  
Marvin Kastner ◽  
Nicole Nellen ◽  
Anne Schwientek ◽  
Carlos Jahn
Keyword(s):  
Random Search ◽  
Time Windows ◽  
Container Terminals ◽  
Bayesian Optimization ◽  
Operational Decisions ◽  
Integrated Simulation ◽  
Cargo Handling ◽  
The Best Approximation ◽  
Simulation Based ◽  
Simulation Based Optimization

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.

scholarly journals Simulation-Based Optimization for Storage Allocation Problem of Outbound Containers in Automated Container Terminals

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Ning Zhao ◽  
Mengjue Xia ◽  
Chao Mi ◽  
Zhicheng Bian ◽  
Jian Jin
Keyword(s):  
Handling Time ◽  
Optimization Method ◽  
Allocation Problem ◽  
Container Terminals ◽  
Storage Allocation ◽  
Swarm Optimization ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Key Factor ◽  
Outbound Containers

Storage allocation of outbound containers is a key factor of the performance of container handling system in automated container terminals. Improper storage plans of outbound containers make QC waiting inevitable; hence, the vessel handling time will be lengthened. A simulation-based optimization method is proposed in this paper for the storage allocation problem of outbound containers in automated container terminals (SAPOBA). A simulation model is built up by Timed-Colored-Petri-Net (TCPN), used to evaluate the QC waiting time of storage plans. Two optimization approaches, based on Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), are proposed to form the complete simulation-based optimization method. Effectiveness of this method is verified by experiment, as the comparison of the two optimization approaches.

scholarly journals Simulation-Based Optimization for Yard Design at Mega Container Terminal under Uncertainty

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Yong Zhou ◽  
Wenyuan Wang ◽  
Xiangqun Song ◽  
Zijian Guo
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Cost Effective ◽  
Container Terminals ◽  
Design Solution ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Uncertain Future ◽  
Reliable Design ◽  
Terminal Operations

The conventional approach of designing a container yard should be reexamined in the context of sustainable port development. Considering the uncertain future throughput, a simulation-based optimization framework is proposed to obtain a cost-effective and reliable design solution to the physical layout and equipment deployment strategy of the yard at a mega container terminal. In this framework, a two-stage stochastic programming model is presented aided with a simulation procedure of terminal operations. Finally, an application is given and the results show that the proposed integrated decision framework is effective and helpful for optimizing container yard design in the context of sustainable development of container terminals.

scholarly journals A Simulation-Based Optimization Approach for Integrated Port Resource Allocation Problem

2014 ◽  
Vol 26 (3) ◽  
pp. 243-255 ◽  
Author(s):  
Gholamreza Ilati ◽  
Abdorreza Sheikholeslami ◽  
Erfan Hassannayebi
Keyword(s):  
Objective Function Value ◽  
Operating Cost ◽  
Allocation Problem ◽  
Container Terminals ◽  
Optimization Approach ◽  
Berth Allocation ◽  
Arrival Times ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Tidal Variations

Todays, due to the rapid increase in shipping volumes, the container terminals are faced with the challenge to cope with these increasing demands. To handle this challenge, it is crucial to use flexible and efficient optimization approach in order to decrease operating cost. In this paper, a simulation-based optimization approach is proposed to construct a near-optimal berth allocation plan integrated with a plan for tug assignment and for resolution of the quay crane re-allocation problem. The research challenges involve dealing with the uncertainty in arrival times of vessels as well as tidal variations. The effectiveness of the proposed evolutionary algorithm is tested on RAJAEE Port as a real case. According to the simulation result, it can be concluded that the objective function value is affected significantly by the arrival disruptions. The result also demonstrates the effectiveness of the proposed simulation-based optimization approach.

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