scholarly journals Minimization of Delay and Travel Time of Yard Trucks in Container Terminals Using an Improved GA with Guidance Search

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Z. X. Wang ◽  
Felix T. S. Chan ◽  
S. H. Chung ◽  
Ben Niu
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Container Terminal ◽  
Container Terminals ◽  
Computational Time ◽  
Small Scale ◽  
Storage Allocation ◽  
Total Delay ◽  
Truck Scheduling ◽  
Np Hard Problem

Yard truck scheduling and storage allocation problems (YTS-SAP) are two important issues that influence the efficiency of a container terminal. These two problems aim to determine the routing of trucks and proper storage locations for discharging containers from incoming vessels. This paper integrates YTS and SAP as a whole and tries to minimize the weighted summation of total delay and total yard trucks travel time. A genetic algorithm (GA) is proposed to deal with the problem. In the proposed GA, guidance mutation approach and exhaustive heuristic for local searching are used in order to force the GA to converge faster and be steadier. To test the performance of the proposed GA, both small scale and large scale cases are studied. The results of these cases are compared with CPLEX for the small scale cases. Since this problem is an NP-hard problem, which CPLEX cannot solve, a simple GA is studied for comparison in large scale cases. The comparison demonstrates that the proposed GA can obtain near optimal solutions in much shorter computational time for small scale cases. In addition, the proposed GA can obtain better results than other methods in reasonable time for large scale cases.

scholarly journals Truck Appointment System for Cooperation between the Transport Companies and the Terminal Operator at Container Terminals

2020 ◽  
Vol 11 (1) ◽  
pp. 168
Author(s):  
Hyeonu Im ◽  
Jiwon Yu ◽  
Chulung Lee
Keyword(s):  
Large Scale ◽  
Container Terminal ◽  
Container Terminals ◽  
The Past ◽  
Cooperation Model ◽  
Appointment System ◽  
New Form ◽  
Truck Appointment System ◽  
Import Container ◽  
Very High

Despite the number of sailings canceled in the past few months, as demand has increased, the utilization of ships has become very high, resulting in sudden peaks of activity at the import container terminals. Ship-to-ship operations and yard activity at the container terminals are at their peak and starting to affect land operations on truck arrivals and departures. In response, a Truck Appointment System (TAS) has been developed to mitigate truck congestion that occurs between the gate and the yard of the container terminal. The vehicle booking system is developed and operated in-house at large-scale container terminals, but efficiency is low due to frequent truck schedule changes by the transport companies (forwarders). In this paper, we propose a new form of TAS in which the transport companies and the terminal operator cooperate. Numerical experiments show that the efficiency of the cooperation model is better by comparing the case where the transport company (forwarder) and the terminal operator make their own decision and the case where they cooperate. The cooperation model shows higher efficiency as there are more competing transport companies (forwarders) and more segmented tasks a truck can reserve.

A New Memetic Approach to Solve the Strategic Berth Template Problem

2021 ◽  
Vol 12 (3) ◽  
pp. 212-231
Author(s):  
Issam El Hammouti ◽  
Azza Lajjam ◽  
Mohamed El Merouani
Keyword(s):  
Large Scale ◽  
Container Terminal ◽  
Mathematical Formulation ◽  
Population Based ◽  
Allocation Problem ◽  
Computational Time ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Simulating Annealing ◽  
Annealing Algorithm

The berth allocation problem is one of the main concerns of port operators at a container terminal. In this paper, the authors study the berth allocation problem at the strategic level commonly known as the strategic berth template problem (SBTP). This problem aims to find the best berth template for a set of calling ships accepted to be served at the port. At strategic level, port operator can reject some ships to be served for avoid congestion. Since the computational complexity of the mathematical formulation proposed for SBTP, solution approaches presented so far for the problem are limited especially at level of large-scale instances. In order to find high quality solutions with a short computational time, this work proposes a population based memetic algorithm which combine a first-come-first-served (FCFS) technique, two genetics operators, and a simulating annealing algorithm. Different computational experiences and comparisons against the best known solutions so far have been presented to show the performance and effectiveness of the proposed method.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2018 ◽  
Author(s):  
Feng Jie Zheng ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Pressure Fluctuation ◽  
Large Scale ◽  
Three Dimensional ◽  
Industrial Process ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial process. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operation such as rapid valve opening/closing. To investigate the pressure especially the pressure fluctuation in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled by a zero-dimensional virtual point, the pipe is modeled by a one-dimensional MOC, and the valve is modeled by a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted, in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve are obtained. The results show that the proposed model is in good agreement with the full CFD model in both large-scale and small-scale spaces. Moreover, the proposed model is more computationally efficient than the CFD model, which provides a feasibility in the analysis of complex RPV system within an affordable computational time.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Feng Jie Zheng ◽  
Chao Yong Zong ◽  
William Dempster ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Large Scale ◽  
Pressure Fluctuations ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Dimensional System ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial processes. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operations such as rapid valve opening or closing. To investigate the pressure response, with particular interest in the pressure fluctuations in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled as a zero-dimensional virtual point, the pipe is modeled as a one-dimensional system using the MOC, and the valve is modeled using a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve is obtained. The results show that the proposed model is in good agreement when compared with a high fidelity CFD model used to represent both large-scale and small-scale spaces. As expected, the proposed model is significantly more computationally efficient than the CFD model. This demonstrates the feasibility of analyzing complex RPV systems within an affordable computational time.

Optimizing Solution for Storage Space Allocation Problem in Container Terminal Using Genetic Algorithm

2016 ◽  
pp. 159-184
Author(s):  
Gamal Abd El-Nasser A. Said ◽  
El-Sayed M. El-Horbaty
Keyword(s):  
Genetic Algorithm ◽  
Service Time ◽  
Container Terminal ◽  
Study Data ◽  
Allocation Problem ◽  
Container Terminals ◽  
Storage Space ◽  
Space Allocation ◽  
Storage Space Allocation ◽  
Np Hard Problem

Seaport container terminals are essential nodes in sea cargo transportation networks. In container terminal, one of the most important performance measures in container terminals is the service time. Storage space allocation operations contribute to minimizing the vessel service time. Storage space allocation problem at container terminals is a combinatorial optimization NP-hard problem. This chapter proposes a methodology based on Genetic Algorithm (GA) to optimize the solution for storage space allocation problem. A new mathematical model that reflects reality and takes into account the workload balance among different types of storage blocks to avoid bottlenecks in container yard operations is proposed. Also the travelling distance between vessels berthing positions and storage blocks at container yard is considered in this research. The proposed methodology is applied on a real case study data of container terminal in Egypt. The computational results show the effectiveness of the proposed methodology.

WAVELET-BASED POSTPROCESSING OF JET LES DATA FOR ACOUSTIC FAR-FIELD EXTRAPOLATIONS

2013 ◽  
Vol 21 (04) ◽  
pp. 1350017
Author(s):  
RAMIN KAVIANI ◽  
VAHID ESFAHANIAN ◽  
MOHAMMAD EBRAHIMI
Keyword(s):  
Large Scale ◽  
Stokes Equations ◽  
Near Field ◽  
Flow Simulation ◽  
Computational Time ◽  
Jet Flows ◽  
Small Scale ◽  
Frequency Noise ◽  
Far Field ◽  
Noise Sources

The affordable grid resolutions in conventional large-eddy simulations (LESs) of high Reynolds jet flows are unable to capture the sound generated by fluid motions near and beyond the grid cut-off scale. As a result, the frequency spectrum of the extrapolated sound field is artificially truncated at high frequencies. In this paper, a new method is proposed to account for the high frequency noise sources beyond the resolution of a compressible flow simulation. The large-scale turbulent structures as dominant radiators of sound are captured in LES, satisfying filtered Navier–Stokes equations, while for small-scale turbulence, a Kolmogorov's turbulence spectrum is imposed. The latter is performed via a wavelet-based extrapolation to add randomly generated small-scale noise sources to the LES near-field data. Further, the vorticity and instability waves are filtered out via a passive wavelet-based masking and the whole spectrum of filtered data are captured on a Ffowcs-Williams/Hawkings (FW-H) surface surrounding the near-field region and are projected to acoustic far-field. The algorithm can be implemented as a separate postprocessing stage and it is observed that the computational time is considerably reduced utilizing a hybrid of many-core and multi-core framework, i.e. MPI-CUDA programming. The comparison of the results obtained from this procedure and those from experiments for high subsonic and transonic jets, shows that the far-field noise spectrum agree well up to 2 times of the grid cut-off frequency.

scholarly journals Method for Reliable Shortest Path Determination in Stochastic Networks using Parametrically Defined Stable Probability Distributions

2019 ◽  
Vol 18 (3) ◽  
pp. 558-582
Author(s):  
Anton Agafonov ◽  
Vladislav Myasnikov
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Road Network ◽  
Large Scale ◽  
Probability Distributions ◽  
Time Budget ◽  
Stochastic Networks ◽  
Computational Time ◽  
Transport Networks ◽  
The Road

An increase in the number of vehicles, especially in large cities, and inability of the existing road infrastructure to distribute transport flows, leads to a higher congestion level in transport networks. This problem makes the solution to navigational problems more and more important. Despite the popularity of these tasks, many existing commercial systems find a route in deterministic networks, not taking into account the time-dependent and stochastic properties of traffic flows, i.e. travel time of road links is considered as constant. This paper addresses the reliable routing problem in stochastic networks using actual information of the traffic flow parameters. We consider the following optimality criterion: maximization of the probability of arriving on time at a destination given a departure time and a time budget. The reliable shortest path takes into account the variance of the travel time of the road network segments, which makes it more applicable for solving routing problems in transport networks compared to standard shortest path search algorithms that take into account only the average travel time of network segments. To describe the travel time of the road network segments, it is proposed to use parametrically defined stable Levy probability distributions. The use of stable distributions allows replacing the operation of calculating convolution to determine the reliability of the path to recalculating the parameters of the distributions density, which significantly reduces the computational time of the algorithm. The proposed method gives a solution in the form of a decision, i.e. the route proposed in the solution is not fixed in advance, but adaptively changes depending on changes in the real state of the network. An experimental analysis of the algorithm carried out on a large-scale transport network of Samara, Russia, showed that the presented algorithm can significantly reduce the computational time of the reliable shortest path algorithm with a slight increase in travel time.

A decision support method for internal truck employment

2014 ◽  
Vol 114 (9) ◽  
pp. 1378-1395 ◽  
Author(s):  
Z.X. Wang ◽  
Felix T.S. Chan ◽  
S.H. Chung ◽  
Ben Niu
Keyword(s):  
Cost Effective ◽  
Empirical Method ◽  
Container Terminals ◽  
Storage Allocation ◽  
Content Type ◽  
Truck Scheduling ◽  
Integration Problem ◽  
The Cost

Purpose – The purpose of this paper is to propose a model that determines the strategy of owning and renting trucks in combinations with internal truck scheduling and storage allocation problems in container terminals. Design/methodology/approach – To deal with this complicated problem, a two-level heuristic approach is developed, in which the integration problem is decomposed into two levels. The first level determines the daily operations of the internal trucks, while the second level determines the truck employment strategy based on the calculation in the first level. Findings – The results show that: even if the using cost of owned yard trucks is much lower than the cost of rented yard tucks, terminal companies should not purchase too many trucks when the purchasing price is high. In addition, the empirical truck employment strategies, which are purchasing all the trucks or renting all the trucks, are not cost-effective when compared with the proposed yard truck employment strategy. Originality/value – The paper provides a novel insight for the internal truck employment strategy in container terminals which is the determination of the strategy of employing renting and outsourcing yard trucks to meet operational daily transportation requirements and minimize the long-term cost of employing yard trucks. A mathematical model is proposed to deal with the practical problem. Also, this study presents better solution than empirical method for employing different types of yard truck. Thus, in order to obtain more benefit, terminal companies should employ the proposed yard truck employment strategy.

scholarly journals Modeling and Design of Container Terminal Operations

2020 ◽  
Vol 68 (3) ◽  
pp. 686-715 ◽  
Author(s):  
Debjit Roy ◽  
René De Koster ◽  
René Bekker
Keyword(s):  
Large Scale ◽  
Container Terminal ◽  
Heavy Traffic ◽  
Building Blocks ◽  
Transport Processes ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Design Parameters ◽  
Container Terminal Operations ◽  
Terminal Operations

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.

scholarly journals Towards fast large-scale flood simulations using 2D Shallow water modelling with depth-dependant porosity

2020 ◽  
Author(s):  
Vita Ayoub ◽  
Carole Delenne ◽  
Patrick Matgen ◽  
Pascal Finaud-Guyot ◽  
Renaud Hostache
Keyword(s):  
Shallow Water ◽  
Spatial Data ◽  
Large Scale ◽  
Model Performance ◽  
Water Model ◽  
Computational Time ◽  
Small Scale ◽  
Test Case ◽  
Strong Impact ◽  
Flood Simulations

<p><span>In hydrodynamic modelling, the mesh resolution has a strong impact on run time and result accuracy. Coarser meshes allow faster simulations but often at the cost of accuracy. Conversely, finer meshes offer a better description of complex geometries but require much longer computational time, which makes their use at a large scale challenging. In this context, we aim to assess the potential of a two-dimensional shallow water model with depth-dependant porosity (SW2D-DDP) for flood simulations at a large scale. This modelling approach relies on nesting a sub-grid mesh containing high-resolution topographic and bathymetric data within each computational cell via a so-called depth-dependant storage porosity. It enables therefore faster simulations on rather coarse grids while preserving small-scale topography information. The July 2007 flood event in the Severn River basin (UK) is used as a test case, for which hydrometric measurements and spatial data are available for evaluation. A sensitivity analysis is carried out to investigate the porosity influence on the model performance in comparison with other classical parameters such as boundary conditions.</span></p>

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