Intelligent scheduling algorithm based on the flow balance control of multipath network

2014 ◽  
Author(s):  
Yi Qian ◽  
Zuxin Li
Keyword(s):  
Balance Control ◽  
Scheduling Algorithm ◽  
Flow Balance ◽  
Intelligent Scheduling

An intelligent scheduling algorithm for complex manufacturing system simulation with frequent synchronizations in a cloud environment

2019 ◽  
Vol 11 (4) ◽  
pp. 357-370 ◽  
Author(s):  
Feng Yao ◽  
Yiping Yao ◽  
Lining Xing ◽  
Huangke Chen ◽  
Zhongwei Lin ◽  
...  
Keyword(s):  
Manufacturing System ◽  
System Simulation ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Intelligent Scheduling

scholarly journals The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

2020 ◽  
Vol 12 (11) ◽  
pp. 168781402097588
Author(s):  
Hanyang Li ◽  
Chao Wang ◽  
Sheng Jiang ◽  
Sheng Liu ◽  
Yiming Rong ◽  
...  
Keyword(s):  
Scheduling Algorithm ◽  
Space Time ◽  
Process Time ◽  
Utilization Rate ◽  
Production Cycle ◽  
Dynamic Priority ◽  
Coupling Constraints ◽  
Full Production ◽  
Complex Constraints ◽  
Intelligent Scheduling

Roller grinding workshop is a typical multi-unit and multi-task manufacturing scenario, which is aimed to repair the surface damage of the rollers caused by the rolling process, so that the rollers can be reused. Due to the process complexity of roller grinding workshop and the large volume and weight of the roller, hoisting and transportation mode with multiple cranes is required. Consequently, the scheduling of the roller grinding workshop needs to consider both the task sequencing in time and the noninterference of the multi-crane trajectory in space. In this paper, the intelligent scheduling of roller grinding workshop is studied based on the characteristics of complex tasks and space-time coupling constraints. Firstly, the scheduling basis is established based on priority rules and process constraints. In order to solve the scheduling problem under the space-time coupling constraints, the position coordinate system is established, and then the algorithms of crane position tracking and cooperative motion without interference are developed. Further, considering the transportation time of crane and its out of sync time point with the processes, the intelligent decision and scheduling algorithm are developed based on the dynamic priority strategy defined to realize scheduling, including time decision, crane decision, and process decision. With the developed intelligent scheduling algorithm applied, the simulation of the roller grinding workshop is conducted under three combinations of priority strategy and noninterference strategy to verify algorithm performance. Under the guarantee of crane noninterference during the full production, the efficiency is improved by 22.1% compared with the existing processing mode of industry. Additionally, EPTR (effective process time rate) based on dynamic priority strategy and noninterference strategy B is up to 100% to avoid intervals between two processes in the scheduling. The dynamic priority developed in this paper reveals more efficiency than MOR principle, while with the strategy B the CUR (crane utilization rate) can be improved more than 20% under the condition of enough machines which facilitates to obtain shorter makespan than strategy A. The intelligent scheduling algorithm developed guarantees the effectiveness and rationality of scheduling with multi-unit and multi-task under the complex constraints. Finally, in order to realize the automatic and intelligent operation of the roller grinding workshop, the management software of the roller grinding workshop is developed by integrating the intelligent scheduling algorithm, which realizes the intelligent production, monitoring, and management of the roller grinding workshop during the full production cycle.

Taxi Intelligent Dispatch System Based on GPS

2013 ◽  
Vol 742 ◽  
pp. 463-468
Author(s):  
Zhong Min Yao ◽  
Zhao Peng Long ◽  
Qiang Li
Keyword(s):  
Mobile Phones ◽  
Time Complexity ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Positioning System ◽  
Traffic Jam ◽  
Gps Positioning ◽  
Dispatch System ◽  
Intelligent Scheduling

GPS positioning system is installed in taxis and most mobile phones support GPS positioning function at present. GPS phones are used in the taxi to achieving intelligent scheduling based on this basis. The taxi intelligent dispatch system based on GPS is proposed, improve the traditional Dijkstra scheduling algorithms by setting taxi maximum reasonable scheduling range, experimental results show that improved algorithms reduce the time complexity and improve scheduling efficiency. Meanwhile the traffic jam information can be sent to the dispatch center and make scheduling algorithm more reasonable by combined with above information.

DDQN-TS: A novel bi-objective intelligent scheduling algorithm in the cloud environment

2021 ◽  
Author(s):  
Zhao Tong ◽  
Feng Ye ◽  
Bilan Liu ◽  
Jinhui Cai ◽  
Jing Mei
Keyword(s):  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Intelligent Scheduling

scholarly journals A Bionic-Intelligent Scheduling Algorithm for Distributed Power Generation System

2021 ◽  
Author(s):  
Zhili Ma ◽  
Zhenzhen Wang ◽  
Yuhong Zhang
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Scheduling Algorithm ◽  
Convergence Speed ◽  
Distributed Energy ◽  
Distributed Power ◽  
Distributed Power Generation ◽  
Intelligent Scheduling ◽  
Pumped Storage ◽  
Power Generation Systems

With the introduction of the new power system concept, diversified distributed power generation systems, such as wind power, photovoltaics, and pumped storage, account for an increasing proportion of the energy supply side. Facing objective issues such as distributed energy decentralization and remote location, exploring what kind of algorithm to use to dispatch nearby distributed energy has become a hot spot in the current electric power field. In view of the current situation, this paper proposes a Bionic Intelligent Scheduling Algorithm (DWMFO) for distributed power generation systems. On the basis of the Moth Flame Algorithm (MFO), in order to solve the problem of low accuracy and slow convergence speed of the algorithm in scheduling distributed energy, we use the adaptive dynamic change factor strategy to dynamically adjust the weighting factor of the MFO. The purpose is to assist the power dispatching department to dispatch diversified distributed energy sources such as wind power, photovoltaics, and pumped storage in a timely manner during the peak power consumption period. In the experiment, we compared with 4 algorithms. The simulation results of 9 test functions show that the optimization performance of DWMFO is significantly improved, the convergence speed is faster, the solution accuracy is higher, and the global search capability is stronger. Experimental test results show that the proposed bionic intelligent scheduling algorithm can expand the effective search space of distributed energy. To a certain extent, the possibility of searching for the global optimal solution is also increased, and a better flame solution can be found.

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