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

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.

2021 ◽  
Vol 2021 ◽  
pp. 1-27
Author(s):  
Shanchuan Yu ◽  
Yuchuan Du ◽  
Jindong Wang ◽  
Yishun Li ◽  
Yong Zhu

This study presents an approach of simulation-based optimization to the operation of the toll plaza at the car park exit. We first propose a simulation model, as the representation of the queueing system for the toll plaza with mixed-type customers and servers where the service time is dependent on the waiting time of customer. Then, a simulation-based integer programming model is developed to design more traffic-efficient yet cost-effective operation schemes. It is decomposed by a rolling horizon approach into subproblems which are all solved via the Kriging metamodel algorithm. A numerical example is presented to illustrate the model and offer insight on how to achieve traffic efficiency and cost-effectiveness.


2021 ◽  
Vol 11 (15) ◽  
pp. 6922
Author(s):  
Jeongmin Kim ◽  
Ellen J. Hong ◽  
Youngjee Yang ◽  
Kwang Ryel Ryu

In this paper, we claim that the operation schedule of automated stacking cranes (ASC) in the storage yard of automated container terminals can be built effectively and efficiently by using a crane dispatching policy, and propose a noisy optimization algorithm named N-RTS that can derive such a policy efficiently. To select a job for an ASC, our dispatching policy uses a multi-criteria scoring function to calculate the score of each candidate job using a weighted summation of the evaluations in those criteria. As the calculated score depends on the respective weights of these criteria, and thus a different weight vector gives rise to a different best candidate, a weight vector can be deemed as a policy. A good weight vector, or policy, can be found by a simulation-based search where a candidate policy is evaluated through a computationally expensive simulation of applying the policy to some operation scenarios. We may simplify the simulation to save time but at the cost of sacrificing the evaluation accuracy. N-RTS copes with this dilemma by maintaining a good balance between exploration and exploitation. Experimental results show that the policy derived by N-RTS outperforms other ASC scheduling methods. We also conducted additional experiments using some benchmark functions to validate the performance of N-RTS.


2013 ◽  
Vol 446-447 ◽  
pp. 1334-1339 ◽  
Author(s):  
Seyed Hamidreza Sadeghian ◽  
Mohd Khairol Anuar Bin Mohd Ariffin ◽  
Say Hong Tang ◽  
Napsiah Binti Ismail

Automation of the processes at the quays of the world's large container ports is one of the answers to the required ever-increasing transshipment volumes within the same timeframe. For such purpose, using new generation of vehicles is unavoidable. One of the automatic vehicles that can be used in container terminals is Automated Lifting Vehicle (ALV). Integrated scheduling of handling equipments with quay cranes can increase the efficiency of automated transport systems in container. In this paper, an integrated scheduling of quay cranes and automated lifting vehicles with limited buffer space is formulated as a mixed integer linear programming model. This model minimizes the makespan of all the loading and unloading tasks for a pre-defined set of cranes in a scheduling problem.


2020 ◽  
Vol 68 (3) ◽  
pp. 686-715 ◽  
Author(s):  
Debjit Roy ◽  
René De Koster ◽  
René Bekker

The design of container terminal operations is complex because multiple factors affect operational performance. These factors include numerous choices for handling technology, terminal topology, and design parameters and stochastic interactions between the quayside, stackside, and vehicle transport processes. In this research, we propose new integrated queuing network models for rapid design evaluation of container terminals with automated lift vehicles and automated guided vehicles. These models offer the flexibility to analyze alternate design variations and develop insights. For instance, the effect of different vehicle dwell point policies and efficient terminal layouts are analyzed. We show the relation among the dwell point–dependent waiting times and also show their asymptotic equivalence at heavy traffic conditions. These models form the building blocks for design and analysis of large-scale terminal operations. We test the model efficacy using detailed simulation experiments and real-terminal validation.


Author(s):  
Lingxiao Wu ◽  
Shuaian Wang

This paper discusses tactical joint quay crane (QC) and yard crane (YC) deployment in container terminals. The deployments of QCs and YCs are critical for the efficiency of container terminals. Although they are closely intertwined, the deployments of QCs and YCs are usually sequential. This paper proposes a mixed-integer programming model for the joint deployment of QCs and YCs in container terminals. The objective of the model is to minimize the weighted vessel turnaround time and the weighted delayed workload for external truck service in yard blocks, both of great importance for a container terminal but rarely considered together in the literature. This paper proves that the studied problem is NP-hard in the strong sense. Case studies demonstrate that the proposed model can obtain better solutions than the sequential method. This paper also investigates the most effective combinations of QCs and YCs for a container terminal at various demand levels.


2021 ◽  
Vol 9 (5) ◽  
pp. 527
Author(s):  
Armi Kim ◽  
Hyun-Ji Park ◽  
Jin-Hyoung Park ◽  
Sung-Won Cho

The rapid increase in international trade volume has caused frequent fluctuation of the vessels’ arrival time in container terminals. In order to solve this problem, this study proposes a methodology for rescheduling berth and quay cranes caused by updated information on the arrival time of vessels. A mixed-integer linear programming model was formulated for the berth allocation and crane assignment problem, and we solved the problem using a rolling-horizon approach. Numerical experiments were conducted under three scenarios with empirical data from a container terminal located in Busan, Korea. The experiments revealed that the proposed model reduces penalty costs and overall delayed departure time compared to the results of the terminal planner.


Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2236
Author(s):  
Hsien-Pin Hsu ◽  
Chia-Nan Wang ◽  
Hsin-Pin Fu ◽  
Thanh-Tuan Dang

The joint scheduling of quay cranes (QCs), yard cranes (YCs), and yard trucks (YTs) is critical to achieving good overall performance for a container terminal. However, there are only a few such integrated studies. Especially, those who have taken the vessel stowage plan (VSP) into consideration are very rare. The VSP is a plan assigning each container a stowage position in a vessel. It affects the QC operations directly and considerably. Neglecting this plan will cause problems when loading/unloading containers into/from a ship or even congest the YT and YC operations in the upstream. In this research, a framework of simulation-based optimization methods have been proposed firstly. Then, four kinds of heuristics/metaheuristics has been employed in this framework, such as sort-by-bay (SBB), genetic algorithm (GA), particle swarm optimization (PSO), and multiple groups particle swarm optimization (MGPSO), to deal with the yard crane scheduling problem (YCSP), yard truck scheduling problem (YTSP), and quay crane scheduling problem (QCSP) simultaneously for export containers, taking operational constraints into consideration. The objective aims to minimize makespan. Each of the simulation-based optimization methods includes three components, load-balancing heuristic, sequencing method, and simulation model. Experiments have been conducted to investigate the effectiveness of different simulation-based optimization methods. The results show that the MGPSO outperforms the others.


2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Ning Zhao ◽  
Mengjue Xia ◽  
Chao Mi ◽  
Zhicheng Bian ◽  
Jian Jin

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.


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