scholarly journals A Dynamic Scheduling Method for Carrier Aircraft Support Operation under Uncertain Conditions Based on Rolling Horizon Strategy

2018 ◽  
Vol 8 (9) ◽  
pp. 1546 ◽  
Author(s):  
Peilong Yuan ◽  
Wei Han ◽  
Xichao Su ◽  
Jie Liu ◽  
Jingyu Song
Keyword(s):  
Renewable Resources ◽  
Large Scale ◽  
Dynamic Scheduling ◽  
Dynamic Environment ◽  
Optimization Method ◽  
Scheduling Problem ◽  
Rolling Horizon ◽  
Scheduling Strategy ◽  
Mutation Strategy ◽  
Event Driven

The efficient scheduling of carrier aircraft support operations in the flight deck is important for battle performances. The supporting operations and maintenance processes involve multiple support resources, complex scheduling process, and multiple constraints; the efficient coordination of these processes can be considered a multi-resource constrained multi-project scheduling problem (MRCMPSP), which is a complex non-deterministic polynomial-time hard (NP-hard) problem. The renewable resources include the operational crews, resource stations, and operational spaces, and the non-renewable resources include oil, gas, weapons, and electric power. An integer programming mathematical model is established to solve this problem. A periodic and event-driven rolling horizon (RH) scheduling strategy inspired by the RH optimization method from predictive control technology is presented for the dynamic scheduling environment. The periodic horizon scheduling strategy can track the changes of the carrier aircraft supporting system, and the improved event-driven mechanism can avoid unnecessary scheduling with effective resource allocation under uncertain conditions. The dual population genetic algorithm (DPGA) is designed to solve the large-scale scheduling problem. The activity list encoding method is proposed, and a new adaptive crossover and mutation strategy is designed to improve the global exploration ability. The double schedule for leftward and rightward populations is integrated into the genetic process of alternating iterations to improve the convergence speed and decrease the computation amount. The computational results show that our approach is effective at solving the scheduling problem in the dynamic environment, as well as making better decisions regarding disruption on a real-time basis.

scholarly journals Berth Allocation Problem with Quay Crane Assignment for Container Terminals Based on Rolling-Horizon Strategy

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Ling Xiao ◽  
Zhi-Hua Hu
Keyword(s):  
Large Scale ◽  
Dynamic Scheduling ◽  
Time Window ◽  
Optimal Solution ◽  
Container Terminals ◽  
Rolling Horizon ◽  
Scheduling Problems ◽  
Berth Allocation Problem ◽  
Arrival Times ◽  
Rolling Window

In order to solve the large-scale integral dynamic scheduling of continuous berths and quay cranes problem, a method based on rolling-horizon strategy is proposed. A multiobjective optimization model that is established minimizes the total penalty costs considering vessels’ deviations to their preferred berthing positions, delayed times for berthing comparing to their estimated arrival times, and delayed times for departure comparing to their estimated departure times. Then, the scheduling process was divided into a set of continual scheduling interval according to the dynamic arrival sequences. Meanwhile, rolling-horizon strategies for setting rolling and frozen windows and the parameter updating strategy are designed. The input parameters of the model in the next rolling window are updated according to the optimal results of each time window which have been obtained. The model is solved by choosing appropriate rolling and freezing window lengths that represents the numbers of adjacent vessels in the sequence of calling vessels. The holistic optimal solution is obtained by gradually rolling and combining the results of each window. Finally, a case study indicated that the rolling schedule can solve large-scale scheduling problems, and the efficiency of the proposed approach relates to the size of rolling window, freeze ship quantity, and rolling frequency.

Scheduling

2010 ◽  
pp. 91-110
Author(s):  
Valentin Cristea ◽  
Ciprian Dobre ◽  
Corina Stratan ◽  
Florin Pop
Keyword(s):  
Distributed Systems ◽  
Large Scale ◽  
Dynamic Scheduling ◽  
Scheduling Algorithms ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Advance Reservation ◽  
Systems Architecture ◽  
Static Versus Dynamic ◽  
Scheduling Models

This chapter presents the scheduling problem in large scale distributed systems. Most parts of the chapter are devoted to discussion of scheduling algorithms and models. The main challenges of scheduling problem are approached here. The implementation issues are also covered. The chapter has three parts. The first part covers basics like scheduling models, scheduling algorithms for independent tasks and DAG scheduling Algorithms for tasks with dependencies. The first part of the chapter presents a classification of scheduling problems, methods that are relevant for the solution procedures, and computational complexity. The scheduling models are presented based on systems architecture described in Resource Management chapter. This firs part also provides a critical analysis of most important algorithms from different points of view, such as static versus dynamic policies, objective functions, applications models, adaptation, QoS constraints and strategies dealing with dynamic behavior of resources. The second part covers new scheduling mechanism like resources co-allocation and advance reservation. Multi-criteria optimization mechanisms for users and systems constrain (e.g. load-balancing, minimization of execution time) are described and analyzed in this chapter. This part uses algorithm and methods to highlight the importance of these topics. The dynamic scheduling is also the subject of this part. It is also presented the implementation issues for scheduler tools. Since it is not possible to cover the whole area of scheduling in one chapter, some restrictions are imposed. Firstly, the chapter presents only Scheduling for Large Scale Distributed Systems (LSDS), without single system scheduling. Secondly, some interesting topics of fault tolerance (re-scheduling) are not analyzed in this chapter.

scholarly journals A Dynamic Scheduling Method of Earth-Observing Satellites by Employing Rolling Horizon Strategy

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Qiu Dishan ◽  
He Chuan ◽  
Liu Jin ◽  
Ma Manhao
Keyword(s):  
Integer Programming ◽  
Dynamic Scheduling ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Scheduling Algorithms ◽  
Scheduling Problem ◽  
Rolling Horizon ◽  
Static Scheduling ◽  
Event Triggering ◽  
Scheduling Method

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments.

scholarly journals Dynamic Scheduling Based on Predicted Inventory Variation Rate for Public Bicycle System

2019 ◽  
Vol 11 (7) ◽  
pp. 1885
Author(s):  
Liang Gao ◽  
Wei Xu ◽  
Yifeng Duan
Keyword(s):  
Dynamic Scheduling ◽  
Process Condition ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Rolling Horizon ◽  
The Public ◽  
Mip Model ◽  
Variation Rate ◽  
Stationary Markov Process

To improve efficiency and reduce the total scheduling cost of the public bicycle system (PBS), dynamic scheduling based on the predicted inventory variation rate (DS-PIVR) is proposed. Regarding a station in the PBS as an inventory system, its inventory variation rate during the scheduling period and its inventory rate at the end of the scheduling period were predicted based on the stationary Markov process condition. A mixed integer programming (MIP) model, whose objective is to minimize the total scheduling distance, was established to describe the dynamic scheduling problem (DSP). Results from Boston and Washington D.C. PBSs show that, when compared to the dynamic scheduling based on the rolling horizon (DS-RH), the DS-PIVR method could at most shorten the routing distance by 62.25% (for Boston) and 74.7% (for Washington D.C.) among all scheduling areas, and could at most shorten the total routing distance for the whole PBS by 21.06% (for Boston) and 17.26% (for Washington D.C.). Moreover, the DS-PIVR method makes the repositioning vehicle journey only once and keeps the inventory rate of each station in balance during the scheduling period. Furthermore, the DS-PIVR method provides a promising reference to improve the operation efficiency by reducing the scheduling cost and the quality of service by satisfying the users’ demand in time during the rush hours for the PBS operators.

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