scholarly journals Adaptive Autotuning Mathematical Approaches for Integrated Optimization of Automated Container Terminal

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Meisu Zhong ◽  
Yongsheng Yang ◽  
Yamin Zhou ◽  
Octavian Postolache
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Operation Mode ◽  
Pso Algorithm ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Mixed Integer ◽  
Integrated Scheduling ◽  
Loading And Unloading ◽  
Unloading Time

With the development of automated container terminals (ACTs), reducing the loading and unloading time of operation and improving the working efficiency and service level have become the key point. Taking into account the actual operation mode of loading and unloading in ACTs, a mixed integer programming model is adopted in this study to minimize the loading and unloading time of ships, which can optimize the integrated scheduling of the gantry cranes (QCs), automated guided vehicles (AGVs), and automated rail-mounted gantries (ARMGs) in automated terminals. Various basic metaheuristic and improved hybrid algorithms were developed to optimize the model, proving the effectiveness of the model to obtain an optimized scheduling scheme by numerical experiments and comparing the different performances of algorithms. The results show that the hybrid GA-PSO algorithm with adaptive autotuning approaches by fuzzy control is superior to other algorithms in terms of solution time and quality, which can effectively solve the problem of integrated scheduling of automated container terminals to improve efficiency.

A New Dispatching Model of Automated Lifting Vehicles in Automated Container Terminal with Limited Buffer Space

2013 ◽  
Vol 446-447 ◽  
pp. 1334-1339 ◽  
Author(s):  
Seyed Hamidreza Sadeghian ◽  
Mohd Khairol Anuar Bin Mohd Ariffin ◽  
Say Hong Tang ◽  
Napsiah Binti Ismail
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Container Terminals ◽  
Mixed Integer ◽  
Transport Systems ◽  
Buffer Space ◽  
Integrated Scheduling ◽  
Quay Cranes ◽  
Automated Lifting Vehicle ◽  
Large Container

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.

Integrated Scheduling of Rail-Mounted Gantry Cranes, Internal Trucks and Reach Stackers in Railway Operation Area of Container Terminal

2018 ◽  
Vol 2672 (9) ◽  
pp. 47-58 ◽  
Author(s):  
Baicheng Yan ◽  
Xiaoning Zhu ◽  
Li Wang ◽  
Yimei Chang
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Container Terminals ◽  
Mixed Integer ◽  
Integrated Scheduling ◽  
Equipment Configuration ◽  
Key Indicators ◽  
Railway Operation ◽  
Gantry Cranes ◽  
Selection Of

In this paper, the integrated scheduling of handling equipment at the railway handling area in container terminals is studied, where rail-mounted gantry cranes, internal trucks, and reach stackers are deployed. In the course of the handling operation, loading and unloading containers are handled simultaneously. The handling process is first studied and some scheduling schemes are put forward. Based on the analysis, the problem is formulated as a mixed-integer programming model, with the objectives of minimizing the makespan and the total waiting time of all equipment. Then, to solve the problem, a genetic algorithm is employed, where the first available machine rule is applied in the selection of trucks and reach stackers. Sets of numerical experiments are conducted to verify the effect of the proposed algorithm. Based on the results of experiments, some key indicators are calculated and the effects of different equipment configuration schemes are studied.

scholarly journals Optimization of Continuous Berth Scheduling by Taking into Account Double-Line Ship Mooring

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Cheng Luo ◽  
Hongying Fei ◽  
Dana Sailike ◽  
Tingyi Xu ◽  
Fuzhi Huang
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Minimum Cost ◽  
Pso Algorithm ◽  
Container Terminals ◽  
Mixed Integer ◽  
Double Line ◽  
Support Tool ◽  
Berth Scheduling ◽  
Operation Cost

“Double-Line Ship Mooring” (DLSM) mode has been applied as an initiative operation mode for solving berth allocation problems (BAP) in certain giant container terminals in China. In this study, a continuous berth scheduling problem with the DLSM model is illustrated and solved with exact and heuristic methods with an objective to minimize the total operation cost, including both the additional transportation cost for vessels not located at their minimum-cost berthing position and the penalties for vessels not being able to leave as planned. First of all, this problem is formulated as a mixed-integer programming model and solved by the CPLEX solver for small-size instances. Afterwards, a particle swarm optimization (PSO) algorithm is developed to obtain good quality solutions within reasonable execution time for large-scale problems. Experimental results show that DLSM mode can not only greatly reduce the total operation cost but also significantly improve the efficiency of berth scheduling in comparison with the widely used single-line ship mooring (SLSM) mode. The comparison made between the results obtained by the proposed PSO algorithm and that obtained by the CPLEX solver for both small-size and large-scale instances are also quite encouraging. To sum up, this study can not only validate the effectiveness of DLSM mode for heavy-loaded ports but also provide a powerful decision support tool for the port operators to make good quality berth schedules with the DLSM mode.

Integrated Scheduling Optimization of Handling Operations in Container Terminal

2013 ◽  
Vol 380-384 ◽  
pp. 4775-4781
Author(s):  
Ji Feng Qian ◽  
Xiao Ning Zhu ◽  
Zhan Dong Liu
Keyword(s):  
Approximate Solution ◽  
Programming Model ◽  
Container Terminal ◽  
Mixed Integer ◽  
Operating Efficiency ◽  
Container Ship ◽  
Scheduling Problem ◽  
Scheduling Optimization ◽  
Integrated Scheduling ◽  
Different Types

In order to improve the efficiency of the handling operations equipment in container terminal, reduce the waiting time of container ship in Port, this paper researches the integrated scheduling of the different types of handling equipment in container terminal, considers the constraints of different handling equipment impact between each other, build a mixed integer programming model, presents a heuristic algorithm for the of the scheduling problem and gets the approximate solution. The results show that the integrated scheduling can effectively reduce the time of the ship staying in port, and improve the overall operating efficiency of the port.

The AFSA-GA Algorithm for the Quay Crane Scheduling Problem of the Loading and Unloading Operations

2017 ◽  
Vol 9 (3) ◽  
pp. 59-71
Author(s):  
Yi Liu ◽  
Sabina Shahbazzade ◽  
Jian Wang
Keyword(s):  
Programming Model ◽  
Global Optimum ◽  
Container Terminals ◽  
Mixed Integer ◽  
Quay Crane Scheduling ◽  
Crane Scheduling ◽  
Ga Algorithm ◽  
Simultaneous Loading ◽  
Loading And Unloading ◽  
Dual Cycle

In order to improve the efficiency of container terminals, eliminate the empty quay cranes movements, the simultaneous loading and unloading operations in same ship-bay is advanced. The AFSA-GA algorithm is proposed to solve the mixed integer programming model of the dual-cycle operation, which take advantage of the strong local search ability of GA and the global optimum search ability of AFSA. The experiment shows that AFSA-GA algorithm can improve the operation efficiency of quay crane significantly.

Integrated Dispatching Model of Automated Lifting Vehicles, Quay Cranes and Yard Cranes at Automated Container Terminal

2014 ◽  
Vol 564 ◽  
pp. 678-683 ◽  
Author(s):  
Seyed Hamidreza Sadeghian ◽  
M.K.A.M. Ariffin ◽  
S.H. Tang ◽  
N. Ismail
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Container Terminal ◽  
Mixed Integer ◽  
Integer Programming Model ◽  
Mixed Integer Programming Model ◽  
Quay Cranes ◽  
Automated Container Terminal ◽  
Loading And Unloading

Integration of various types of handling equipment is one of the important methods to improve the efficiency of processes and productivity of a container terminal. Using ALVs, because of their ability in lifting a container from the ground by themselves, can reduce the delay of loading and unloading tasks in automatic container terminals.In this paper, a mixed-integer programming model, which considers the integration of ALVs, Quay Cranes and Yard Cranes, is developed. This model minimizes the makespan of the loading and unloading activities in an Automatic Container Terminal with limited buffer spaces.

Joint Deployment of Quay Cranes and Yard Cranes in Container Terminals at a Tactical Level

2018 ◽  
Vol 2672 (9) ◽  
pp. 35-46
Author(s):  
Lingxiao Wu ◽  
Shuaian Wang
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Container Terminal ◽  
Turnaround Time ◽  
Container Terminals ◽  
Mixed Integer ◽  
Sequential Method ◽  
Quay Cranes ◽  
Proposed Model

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.

scholarly journals Rescheduling Strategy for Berth Planning in Container Terminals: An Empirical Study from Korea

2021 ◽  
Vol 9 (5) ◽  
pp. 527
Author(s):  
Armi Kim ◽  
Hyun-Ji Park ◽  
Jin-Hyoung Park ◽  
Sung-Won Cho
Keyword(s):  
Mixed Integer Linear Programming ◽  
Arrival Time ◽  
Programming Model ◽  
Container Terminal ◽  
Container Terminals ◽  
Mixed Integer ◽  
Berth Allocation ◽  
Trade Volume ◽  
Penalty Costs ◽  
Proposed Model

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.

scholarly journals Storage Allocation in Automated Container Terminals: the Upper Level

2016 ◽  
Vol 23 (s1) ◽  
pp. 160-174 ◽  
Author(s):  
Xia Mengjue ◽  
Zhao Ning ◽  
Mi Weijian
Keyword(s):  
Programming Model ◽  
Level Structure ◽  
Pso Algorithm ◽  
Container Terminals ◽  
Mixed Integer ◽  
Future Research ◽  
Storage Allocation ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Upper Level

Abstract Nowadays automation is a trend of container terminals all over the world. Although not applied in current automated container terminals, storage allocation is indispensable in conventional container terminals, and promising for automated container terminals in future. This paper seeks into the storage allocation problem in automated container terminals and proposed a two level structure for the problem. A mixed integer programming model is built for the upper level, and a modified Particle Swarm Optimization (PSO) algorithm is applied to solve the model. The applicable conditions of the model is investigated by numerical experiments, so as the performance of the algorithm in different problem scales. It is left to future research the lower level of the problem and the potential benefit of storage allocation to automated container terminals.

scholarly journals Multi Objective Optimization of Coordinated Scheduling of Cranes and Vehicles at Container Terminals

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Seyed Mahdi Homayouni ◽  
Sai Hong Tang
Keyword(s):  
Genetic Algorithm ◽  
Programming Model ◽  
Numerical Test ◽  
Optimal Solution ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Mixed Integer ◽  
Computational Time ◽  
Medium Size ◽  
Coordinated Scheduling

According to previous researches, automated guided vehicles and quay cranes in container terminals have a high potential synergy. In this paper, a mixed integer programming model is formulated to optimize the coordinated scheduling of cranes and vehicles in container terminals. Objectives of the model are to minimize total traveling time of the vehicles and delays in tasks of cranes. A genetic algorithm is developed to solve the problem in reasonable computational time. The most appropriate control parameters for the proposed genetic algorithm are investigated in a medium size numerical test case. It is shown that balanced crossover and mutation rates have the best performance in finding a near optimal solution for the problem. Then, ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the genetic algorithm since it can find near optimal solutions, precisely and accurately.

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