An Investigation into Sidings Allocation Strategy for Automated Container Terminal Based on A* Search Algorithm

2012 ◽  
Vol 472-475 ◽  
pp. 526-532
Author(s):  
Wei Yan ◽  
Yuan Jiang ◽  
Jun Liang He
Keyword(s):  
Waiting Time ◽  
Search Algorithm ◽  
Container Terminal ◽  
Rolling Horizon ◽  
Optimal Solutions ◽  
Dynamic Allocation ◽  
Allocation Strategy ◽  
Actual Case ◽  
Allocation Model ◽  
Automated Container Terminal

A rolling-horizon approach was proposed, which aims at the problem of sidings allocation for automated container yard stacking system designed and invented by ZPMC. The dynamic allocation model using objective programming was initially developed for sidings allocation. The model objective function was subject to the minimization of the total job waiting time. Furthermore A* search algorithm was employed for solving the model, which can return optimal solutions. Finally an actual case was firstly studied to illustrate the proposed approach for sidings allocation strategy, and then verified the validity and usefulness of this model and algorithm.

scholarly journals Cooperative Scheduling of AGV and ASC in Automation Container Terminal Relay Operation Mode

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Qinglei Zhang ◽  
Weixin Hu ◽  
Jianguo Duan ◽  
Jiyun Qin
Keyword(s):  
Waiting Time ◽  
Large Scale ◽  
Buffer Capacity ◽  
Container Terminal ◽  
Operation Mode ◽  
Buffer Zone ◽  
Buffer Zones ◽  
Collaborative Scheduling ◽  
Automated Container Terminal ◽  
Time Buffer

The key problem of operation optimization for automated container terminal is the coordinated scheduling of automated quay crane (QC), automated guided vehicle (AGV), and automated stacking crane (ASC). In order to solve this problem, this paper proposed a new method to optimize the scheduling of ASC and AGV. In the automated container terminal, each container block is equipped with twin ASCs. At the same time, buffer zones are set at both ends of the container block to achieve the decoupling operation among ASC, AGV, and container truck. Considering the buffer capacity constraint and twin ASC operation interference, and introducing the design of handshake area, this paper developed a collaborative scheduling model of AGV and ASC in automatic terminal relay operation mode. This model is designed based on the genetic algorithm. The model aims to minimize the AGV waiting time and the ASC running time. The results indicated that the introduction of handshake area can effectively reduce the ASC operation interference by 10.56% on average. Also, it can be found that increasing buffer capacity can reduce the waiting time of AGV by about 4.25% on average, and the effect of relay operation is more obvious in large-scale operation. It was proved that buffer zone and handshake area can reduce task delay time and improve coordination between AGV and ASC.

scholarly journals Noisy Optimization of Dispatching Policy for the Cranes at the Storage Yard in an Automated Container Terminal

2021 ◽  
Vol 11 (15) ◽  
pp. 6922
Author(s):  
Jeongmin Kim ◽  
Ellen J. Hong ◽  
Youngjee Yang ◽  
Kwang Ryel Ryu
Keyword(s):  
Container Terminal ◽  
Scoring Function ◽  
Weight Vector ◽  
Container Terminals ◽  
Exploration And Exploitation ◽  
Noisy Optimization ◽  
Automated Container Terminal ◽  
Simulation Based ◽  
The Cost ◽  
Operation Schedule

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.

Optimal berth allocation under regular and emergent vessel arrivals

2020 ◽  
pp. 147509022093788
Author(s):  
Abbas Al-Refaie ◽  
Hala Abedalqader
Keyword(s):  
Waiting Time ◽  
Container Terminal ◽  
Allocation Problem ◽  
Container Terminals ◽  
Future Research ◽  
Satisfaction Level ◽  
Berth Allocation ◽  
Scheduling Problems ◽  
Berth Allocation Problem ◽  
Quay Crane Assignment

This research proposes two optimization models to deal with the berth allocation problem. The first model considers the berth allocation problem under regular vessel arrivals to minimize the flow time of vessels in the marine container terminal, minimize the tardiness penalty costs, and maximize the satisfaction level of vessels’ operators on preferred times of departure. The second model optimizes the berth allocation problem under emergency conditions by maximizing the number of assigned vessels, minimizing the vessel’s waiting time, and maximizing the satisfaction level on the served ships. Two real examples are provided for model illustration under regular and emergent vessel arrivals. Results show that the proposed models effectively provide optimal vessel scheduling in the terminal, reduce costs at an acceptable satisfaction level of vessels’ operators, decrease the waiting time of vessels, and shorten the delay in departures under both regular and emergent vessel arrivals. In conclusion, the proposed models may provide valuable assistance to decision-makers in marine container terminals on determining optimal berth allocation under daily and emergency vessel arrivals. Future research considers quay crane assignment and scheduling problems.

scholarly journals An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory

2019 ◽  
Vol 11 (22) ◽  
pp. 6287 ◽  
Author(s):  
Aqib Jamil ◽  
Turki Ali Alghamdi ◽  
Zahoor Ali Khan ◽  
Sakeena Javaid ◽  
Abdul Haseeb ◽  
...  
Keyword(s):  
Game Theory ◽  
Energy Management ◽  
Waiting Time ◽  
Management System ◽  
Search Algorithm ◽  
Energy Management System ◽  
Hybrid Technique ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Home Energy Management System

The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.

A solution method for treatment scheduling in rehabilitation hospitals with real-life requirements

2018 ◽  
Vol 30 (4) ◽  
pp. 367-386 ◽  
Author(s):  
Liyang Xiao ◽  
Mahjoub Dridi ◽  
Amir Hajjam El Hassani ◽  
Wanlong Lin ◽  
Hongying Fei
Keyword(s):  
Waiting Time ◽  
Programming Model ◽  
Search Algorithm ◽  
Real Life ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Mixed Integer ◽  
Solution Quality ◽  
Improved Cuckoo Search Algorithm ◽  
Rehabilitation Hospitals

Abstract In this study, we aim to minimize the total waiting time between successive treatments for inpatients in rehabilitation hospitals (departments) during a working day. Firstly, the daily treatment scheduling problem is formulated as a mixed-integer linear programming model, taking into consideration real-life requirements, and is solved by Gurobi, a commercial solver. Then, an improved cuckoo search algorithm is developed to obtain good quality solutions quickly for large-sized problems. Our methods are demonstrated with data collected from a medium-sized rehabilitation hospital in China. The numerical results indicate that the improved cuckoo search algorithm outperforms the real schedules applied in the targeted hospital with regard to the total waiting time of inpatients. Gurobi can construct schedules without waits for all the tested dataset though its efficiency is quite low. Three sets of numerical experiments are executed to compare the improved cuckoo search algorithm with Gurobi in terms of solution quality, effectiveness and capability to solve large instances.

Geographic Disparity in the United States Heart Allocation System

2019 ◽  
pp. 65-87
Author(s):  
Fatemeh Karami ◽  
Mehdi Nayebpour ◽  
Monica Gentili ◽  
Naoru Koizumi ◽  
Andrew Rivard
Keyword(s):  
United States ◽  
Mortality Rate ◽  
Waiting Time ◽  
Average Distance ◽  
The United States ◽  
Allocation Model ◽  
Geographic Disparity ◽  
Transplant Candidates ◽  
Geographic Equity ◽  
The Impact

Organ allocation for transplantation across the United States is administered by the United Network for Organ Sharing (UNOS). UNOS recently approved a major policy change of the system used to allocate hearts for adult transplant candidates. The main objective of this study is to investigate the impact of the new policy on geographic disparity measured by four performance indicators (waiting time before a transplant, transplant rate, pre-transplant mortality rate, and average distance traveled by donated hearts). The current policy and the new policy were evaluated using the thoracic simulation allocation model. The results show that the new policy improves the median waiting time, transplant rate, and pre-transplant mortality rate. The overall predicted improvement in geographic equity is modest except in terms of waiting time. The findings highlight the need for a targeted approach for donor heart allocation to achieve equal access to heart transplantation in the US.

Performances of Adaptive Cuckoo Search Algorithm in Engineering Optimization

2016 ◽  
pp. 676-699 ◽  
Author(s):  
Pauline Ong ◽  
S. Kohshelan
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Breeding Strategy ◽  
Function Optimization ◽  
Engineering Optimization ◽  
Optimal Solutions ◽  
Step Size ◽  
Swarm Optimization ◽  
Searching Strategy

A new optimization algorithm, specifically, the cuckoo search algorithm (CSA), which inspired by the unique breeding strategy of cuckoos, has been developed recently. Preliminary studies demonstrated the comparative performances of the CSA as opposed to genetic algorithm and particle swarm optimization, however, with the competitive advantage of employing fewer control parameters. Given enough computation, the CSA is guaranteed to converge to the optimal solutions, albeit the search process associated to the random-walk behavior might be time-consuming. Moreover, the drawback from the fixed step size searching strategy in the inner computation of CSA still remain unsolved. The adaptive cuckoo search algorithm (ACSA), with the effort in the aspect of integrating an adaptive search strategy, was attached in this study. Its beneficial potential are analyzed in the benchmark test function optimization, as well as engineering optimization problem. Results showed that the proposed ACSA improved over the classical CSA.

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