scholarly journals Optimization of warship formation air defense combat model based on dynamic scheduling of combat resources

2018 ◽  
Vol 10 (7) ◽  
pp. 168781401878529
Author(s):  
Liang Ma ◽  
Jian-guo Wang
Keyword(s):  
Hybrid Algorithm ◽  
Dynamic Scheduling ◽  
Limited Resources ◽  
Maximum Efficiency ◽  
Allocation Of Resources ◽  
Air Defense ◽  
Defense Strategy ◽  
Scheduling Model ◽  
Simulation Results ◽  
Operational Time

Aiming at the problem of limited resources and operational time combat air defense combat, naval combat formation analysis dynamic resources scheduling needs, on the basis of the establishment of ship dynamic scheduling model of warship formation combat resources dynamic combat formation resource scheduling, the operational resources and operational objectives, relationship between reasonable allocation of resources to play the warship formation combat operations the maximum efficiency. The design of three kinds of air defense command models: centralized platform free attack mode, command mode, request attack mode of air defense strategy, put forward the dynamic scheduling hybrid algorithm for solving the model, according to the naval fleet air defense combat scenario example for simulation. The simulation results show that the air defense strategy with the request attack mode can have effects on multi-target attacks under the shared combat situation, and the hybrid algorithm based on combat resource dynamic scheduling can meet the real-time operational requirements.

Parallel Scheduling Algorithms Investigation of Support Strict Resource Reservation from Grid

2014 ◽  
Vol 519-520 ◽  
pp. 108-113 ◽  
Author(s):  
Jun Chen ◽  
Bo Li ◽  
Er Fei Wang
Keyword(s):  
Parallel Computing ◽  
Resource Utilization ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Resource Reservation ◽  
Parallel Scheduling ◽  
Scheduling Model ◽  
Computing Grid ◽  
Simulation Results ◽  
Reservation Request

This paper studies resource reservation mechanisms in the strict parallel computing grid,and proposed to support the parallel strict resource reservation request scheduling model and algorithms, FCFS and EASY backfill analysis of two important parallel scheduling algorithm, given four parallel scheduling algorithms supporting resource reservation. Simulation results of four algorithms of resource utilization, job bounded slowdown factor and the success rate of Advanced Reservation (AR) jobs were studied. The results show that the EASY backfill + firstfit algorithm can ensure QoS of AR jobs while taking into account the performance of good non-AR jobs.

Dynamic Scheduling Model of Rail-Guided Vehicle (RGV) Based on Genetic Algorithms in the Context of Mobile Computing

2021 ◽  
Vol 12 (1) ◽  
pp. 43-62
Author(s):  
Chen Xu ◽  
Xueyan Xiong ◽  
Qianyi Du ◽  
Shudong Liu ◽  
Yipeng Li ◽  
...  
Keyword(s):  
Information System ◽  
Mobile Computing ◽  
Dynamic Scheduling ◽  
Distributed Processing ◽  
Processing System ◽  
Time Dynamic ◽  
Scheduling Model ◽  
Practical Operation ◽  
Optimization Efficiency ◽  
Production And Operation

Track guidance vehicle (RGV) is widely used in logistics warehousing and intelligent workshop, and its scheduling effectiveness will directly affect the production and operation efficiency of enterprises. In practical operation, central information system often lacks flexibility and timeliness. By contrast, mobile computing can balance the central information system and the distributed processing system, so that useful, accurate, and timely information can be provided to RGV. In order to optimize the RGV scheduling problem in uncertain environment, a genetic algorithm scheduling rule (GAM) using greedy algorithm as the genetic screening criterion is proposed in this paper. In the experiment, RGV scheduling of two-step processing in an intelligent workshop is selected as the research object. The experimental results show that the GAM model can carry out real-time dynamic programming, and the optimization efficiency is remarkable before a certain threshold.

A Hybrid Algorithm of Mining Closed Itemsets for Large Databases

2011 ◽  
Vol 145 ◽  
pp. 292-296
Author(s):  
Lee Wen Huang
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Execution Time ◽  
Hybrid Algorithm ◽  
Hybrid Approach ◽  
Market Basket Analysis ◽  
Market Basket ◽  
Large Databases ◽  
Closed Itemsets ◽  
Simulation Results

Data Mining means a process of nontrivial extraction of implicit, previously and potentially useful information from data in databases. Mining closed large itemsets is a further work of mining association rules, which aims to find the set of necessary subsets of large itemsets that could be representative of all large itemsets. In this paper, we design a hybrid approach, considering the character of data, to mine the closed large itemsets efficiently. Two features of market basket analysis are considered – the number of items is large; the number of associated items for each item is small. Combining the cut-point method and the hash concept, the new algorithm can find the closed large itemsets efficiently. The simulation results show that the new algorithm outperforms the FP-CLOSE algorithm in the execution time and the space of storage.

scholarly journals Timetable Design for Urban Rail Line with Capacity Constraints

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Ting Zhu ◽  
Bao-Hua Mao ◽  
Lu Liu ◽  
Ming-Gao Li
Keyword(s):  
Solution Method ◽  
Operating Cost ◽  
Capacity Constraints ◽  
Scheduling Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line ◽  
First Come First Serve ◽  
Waiting Cost ◽  
Simulation Results

To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.

scholarly journals Application of a Multi-Satellite Dynamic Mission Scheduling Model Based on Mission Priority in Emergency Response

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1430 ◽  
Author(s):  
Jintian Cui ◽  
Xin Zhang
Keyword(s):  
Dynamic Scheduling ◽  
Search Algorithm ◽  
Earth Observation ◽  
Impact Factors ◽  
Scheduling Problem ◽  
Model Based ◽  
Scheduling Model ◽  
Earth Observation Satellites ◽  
Scheduling Plan ◽  
Satellite Scheduling

Emergency observations are missions executed by Earth observation satellites to support urgent ground operations. Emergency observations become more important for meeting the requirements of highly dynamic and highly time-sensitive observation missions, such as disaster monitoring and early warning. Considering the complex scheduling problem of Earth observation satellites under emergency conditions, a multi-satellite dynamic mission scheduling model based on mission priority is proposed in this paper. A calculation model of mission priority is designed for emergency missions based on seven impact factors. In the satellite mission scheduling, the resource constraints of scheduling are analyzed in detail, and the optimization objective function is built to maximize the observation mission priority and mission revenues, and minimize the waiting time for missions that require urgency for execution time. Then, the hybrid genetic tabu search algorithm is used to obtain the initial satellite scheduling plan. In case of the dynamic arrival of new emergency missions before scheduling plan releases, a dynamic scheduling algorithm based on mission priority is proposed to solve the scheduling problem caused by newly arrived missions and to obtain the scheduling plan of newly arrived missions. A simulation experiment was conducted for different numbers of initial missions and newly arrived missions, and the scheduling results were evaluated with a model performance evaluation function. The results show that the execution probability of high-priority missions increased because the mission priority was taken into account in the model. In the case of more satellite resources, when new missions dynamically arrived, the satellite resources can be reasonably allocated to these missions based on the mission priority. Overall, this approach reduces the complexity of the dynamic adjustment and maintains the stability of the initial scheduling plan.

A Method of Generating a Pitch-Up Trajectory Based on a Virtual Target Guidance Law

2010 ◽  
Vol 77 (5) ◽  
Author(s):  
Yu Fu ◽  
Naigang Cui
Keyword(s):  
Long Range ◽  
Engineering Applications ◽  
Air Defense ◽  
Guidance Law ◽  
Parabolic Trajectory ◽  
Virtual Target ◽  
Simulation Results ◽  
Defense Research

The pitch-up trajectory is a high parabolic trajectory. Long range interceptor missiles will be important for future air defense. Research indicates that a high parabolic trajectory can enhance the missile range. A method of generating high parabolic trajectories based on a virtual target guidance law is proposed in this paper. The proposed method is formulated and its effectiveness is demonstrated by two test simulations. The simulation results show that a missile can fly in a high parabolic trajectory with good characteristics using the virtual target guidance law. The proposed method fulfills the current needs and is suited for engineering applications.

A New Joint Data-Model Driven Dynamic Scheduling Architecture for Intelligent Workshop

2019 ◽  
Author(s):  
Kunkun Peng ◽  
Xinyu Li ◽  
Liang Gao ◽  
Xi (Vincent) Wang ◽  
Yiping Gao
Keyword(s):  
Data Model ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Intelligent Manufacturing ◽  
Intelligent Optimization ◽  
Model Driven ◽  
Dynamic Events ◽  
Event Prediction ◽  
Scheduling Model ◽  
Intelligent Optimization Algorithm

Abstract Intelligent manufacturing plays a significant role in Industry 4.0. Dynamic shop scheduling is a key problem and hot research topic in the intelligent manufacturing systems, which is NP-hard. However, traditional shop scheduling mode, dynamic event prediction approach, scheduling model and scheduling algorithm, cannot cope with increasingly complicated problems under kinds of scales production disruptions in the real-world production. To deal with these problems, this paper proposes a new joint data-model driven dynamic scheduling architecture for intelligent workshop. The architecture includes four new and key characteristics in the aspects of scheduling mode, dynamic event prediction, scheduling model and algorithm. More specifically, the new scheduling mode introduces data analytics methods to quickly and accurately deal with the dynamic events encountered in the production process. The new prediction model improves the deep learning method, and further applies it predict the dynamic events accurately to provide reliable input to the dynamic scheduling. The new scheduling model proposes a new hybrid rescheduling and inverse scheduling model, which can cope with almost scales of abnormal production problems. The new scheduling algorithm hybridizes dynamic programming and intelligent optimization algorithm, which can overcome the disadvantages of the two methods based on the analysis of solution space. The dynamic programming is employed to provide high-quality initial solutions for the intelligent optimization algorithm by reducing the computation time greatly. To sum up, the presented architecture is a new attempt to understand the problem domain knowledge and broaden the solving idea, which can also provide new theories and technologies to manufacturing system optimization and promote the applications of the theoretical results.

scholarly journals Dynamic Soft Real-Time Scheduling with Preemption Threshold for Streaming Media

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Wenle Wang ◽  
Yuan Wang ◽  
JiangYan Dai ◽  
Zhonghua Cao
Keyword(s):  
Real Time ◽  
Video Streaming ◽  
Dynamic Scheduling ◽  
Threshold Strategy ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
Simulation Results ◽  
Relationship Of ◽  
Networking Technology ◽  
Efficient Video

Over the last decades, the advancements in networking technology and new multimedia devices have motivated the research on efficient video streaming mechanisms under wireless. We consider combing soft real-time video streaming scheduling with threshold to minimize the ineffective preemption. Based on the value density and urgency of soft real-time task, the dynamic scheduling with preemption threshold strategy (DSPT) is proposed in the paper. By analyzing the response time and preemption relationship of tasks, the preemption thresholds are assigned. Simulation results show that the DSPT strategy achieves improvements about success rate, delay time, and benefit of the system.

Simulation analysis and performance of a feasible GNSS system with multi-beam antennas deployment operating in Galileo frequency bands

2012 ◽  
Vol 4 (5) ◽  
pp. 537-543
Author(s):  
Constantinos T. Angelis
Keyword(s):  
Simulation Analysis ◽  
European Space Agency ◽  
Satellite System ◽  
Access Time ◽  
Maximum Efficiency ◽  
Satellite Systems ◽  
Space Agency ◽  
Simulation Results ◽  
And Performance ◽  
Global Navigation Satellite

New Global Navigation Satellite System (GNSS) systems under development, such as Galileo, are very promising for future global positioning-based applications. A vast research is undergoing a final stage of implementation in order to fulfill the primary purpose of European Space Agency for developing and then sustaining of 30 (27 + 3 spares) Galileo satellites in orbit. This article presents simulation results for a realistic deployment of multibeam antennas, with a new modified theoretical pattern, in GNSS Satellite Systems. The proposed multibeam antennas use 61-spot beams for maximum efficiency in terms of satellite coverage and accessing high quality of service. In order to prove the reliability and feasibility of this work, various simulations were conducted using the upcoming Galileo system as a platform taking into consideration real-world conditions. Gain analysis versus elevation, Bit Error Rate (BER) and access time simulation results show that the viability of the proposed multibeam antenna deployment is established.

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