Study of Dynamic Scheduling Strategy for Large-Scale Terrain Visualization in Flight Simulation System

2016 ◽  
Author(s):  
Gao Qiang ◽  
Ji Ming ◽  
Pang Lan ◽  
Wang Jing ◽  
Song Hui-Juan ◽  
...  
Keyword(s):  
Large Scale ◽  
Dynamic Scheduling ◽  
Simulation System ◽  
Flight Simulation ◽  
Terrain Visualization ◽  
Scheduling Strategy

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 A Data-Aware Scheduling Strategy for Executing Large-Scale Distributed Workflows

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 47354-47364
Author(s):  
Salvatore Giampa ◽  
Loris Belcastro ◽  
Fabrizio Marozzo ◽  
Domenico Talia ◽  
Paolo Trunfio
Keyword(s):  
Large Scale ◽  
Scheduling Strategy

scholarly journals Networked HIL Simulation System for Modeling Large-scale Power Systems

2021 ◽  
Author(s):  
Fuhong Xie ◽  
Catie McEntee ◽  
Mingzhi Zhang ◽  
Ning Lu ◽  
Xinda Ke ◽  
...  
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Simulation System ◽  
Hil Simulation

Intelligent Bidding in Smart Electricity Markets

2017 ◽  
pp. 712-734
Author(s):  
Magda Foti ◽  
Manolis Vavalis
Keyword(s):  
Electricity Markets ◽  
Large Scale ◽  
Electric Energy ◽  
Energy Markets ◽  
Simulation System ◽  
Theoretical Studies ◽  
The Social ◽  
Early Proof ◽  
Simulation Results ◽  
Large Scale Simulations

This paper has two aims. Firstly, to briefly present overall objectives and expected outcome of an on-going effort concerning design, implementation and the analysis of next generation energy systems based on anticipatory control and a set of ICT emerging technologies and innovations. Secondly, to describe an early proof-of-concept implementation and the associated experimentation of a simulation platform focused on holistic detailed studies of electric energy markets. The proposed platform allows us to elucidate issues related to the open and smart participation of producers and consumers on large-scale e-markets. Based on an existing simulation system, the authors present the required theoretical studies, the enabling technologies, and the practical tools that contribute to the development of such a platform capable of truly large scale simulations. Elements of game theory are utilized to solve the optimization problem related to the maximization of the social welfare of producers and consumers. Selected simulation results associated with the basic required characteristics are presented.

Scheduling Large-Scale DNA Sequencing Applications

2010 ◽  
pp. 841-857
Author(s):  
Sudha Gunturu ◽  
Xiaolin Li ◽  
Laurence Tianruo Yang
Keyword(s):  
Large Scale ◽  
Processing Time ◽  
Sequence Length ◽  
Communication Link ◽  
Load Scheduling ◽  
Scheduling Strategy ◽  
Optimal Processing ◽  
Dna Sequence Alignment ◽  
Alignment Algorithms ◽  
Large Scale Networks

This chapter studies a load scheduling strategy with near-optimal processing time that is designed to explore the computational characteristics of DNA sequence alignment algorithms, specifically, the Needleman-Wunsch Algorithm. Following the divisible load scheduling theory, an efficient load scheduling strategy is designed in large-scale networks so that the overall processing time of the sequencing tasks is minimized. In this study, the load distribution depends on the length of the sequence and number of processors in the network and, the total processing time is also affected by communication link speed. Several cases have been considered in the study by varying the sequences, communication and computation speeds, and number of processors. Through simulation and numerical analysis, this study demonstrates that for a constant sequence length as the numbers of processors increase in the network the processing time for the job decreases and minimum overall processing time is achieved.

scholarly journals Variable Stability In-Flight Simulation System Based on Existing Autopilot Hardware

2020 ◽  
Vol 43 (12) ◽  
pp. 2275-2288
Author(s):  
Pepijn A. Scholten ◽  
Marinus M. van Paassen ◽  
Q. Ping Chu ◽  
Max Mulder
Keyword(s):  
Simulation System ◽  
Flight Simulation
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