scholarly journals Serial Combination Optimization Method of Packet Transport Network

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chunzhi Wang ◽  
Zaoning Wang ◽  
Xing Li ◽  
Sha Guan ◽  
Ruoxi Wang
Keyword(s):  
Optimization Algorithm ◽  
Network Architecture ◽  
Formation Rate ◽  
Optimization Method ◽  
Ring Formation ◽  
Transport Network ◽  
Occupancy Rate ◽  
Network Stability ◽  
Network Efficiency ◽  
Combination Optimization

Packet transport network (PTN) has problems such as waste of resources and low network stability due to the excessive complexity of the existing network or improper network architecture design. The optimization of the transport networks can not only make the network structure more reasonable but also reduce all kinds of unexpected scenarios in the network operation, improving the network efficiency and reducing the failure rate. This research will be optimized from three aspects. (1) In order to solve the problem of the same active and standby routing in the existing network, an optimization algorithm for the same active and standby routing of LSP is proposed. The essence of the optimization algorithm is to search the existing routing using the K -shortest path (KSP) between two network nodes as protection routing for LSP protection. (2) Aiming at the link with a high CIR bandwidth occupancy rate, a method is completed without adding optical fibers and other physical resources; an optimization method for the committed information rate bandwidth occupancy rate based on the KSP algorithm is proposed. (3) When the PTN ring formation rate is low, the security of the PTN is seriously reduced. In order to solve the problem of low ring formation rate in the network, this paper proposes a ring formation rate optimization scheme for PTN access layer equipment based on network elements accounting income. Through the experimental verification on the mobile PTN in one city, Hubei Province, the combination optimization method can improve the network LSP protection rate by 24%, the CIR bandwidth occupancy rate is reduced by 13.82%, and the nonring forming rate was reduced by 17.9%. This method improved network stability, reducing the risk of failure in service transportation effectively.

Continuous Ant Colony Algorithm

2011 ◽  
Vol 308-310 ◽  
pp. 1008-1011 ◽  
Author(s):  
Wei Gao
Keyword(s):  
Swarm Intelligence ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Continuous Optimization ◽  
Evolutionary Programming ◽  
Optimization Method ◽  
Good Combination ◽  
Ant Colony ◽  
Combination Optimization ◽  
Searching Performance

Ant Colony Algorithm is a new bionics optimization algorithm from mimic the swarm intelligence of ant colony behavior. And it is a very good combination optimization method. To extend the ant colony algorithm, and to improve the searching performance, from the connections of continuous optimization and searching process of ant colony algorithm, one new Continuous Ant Colony Algorithm is proposed. To verify the new algorithm, the typical functions, such as Schaffer function and “Needle-in-a-haystack” function, are all used. And then, the results of new algorithm are compared with that of immunized evolutionary programming proposed by author.

An Optimization Method for Optimal Engineering Structure Design Combining Intelligent Optimization Algorithm and CAE Code

2011 ◽  
Vol 399-401 ◽  
pp. 2296-2300
Author(s):  
Wen Jie Peng ◽  
Rui Ge ◽  
Ming Kai Gu
Keyword(s):  
Analytical Solution ◽  
Normal Stress ◽  
Optimization Algorithm ◽  
Optimization Method ◽  
Structure Design ◽  
Stacking Sequence ◽  
Intelligent Optimization ◽  
Engineering Structure ◽  
Intelligent Optimization Algorithm ◽  
Computer Aided

This paper presents an optimization method for optimal engineering structure design. An interface procedure is essentially developed to combine the intelligent optimization algorithm and computer aided engineering (CAE) code. An optimization example is carried out to minimize the interlaminar normal stress of a laminate which affect the delamination failure of a laminate via arranging the stacking sequence. The analytical solution is calculated to validate the accuracy of optimization results.

A general trajectory optimization method for aircraft taxiing on flight deck of carrier

2018 ◽  
Vol 233 (4) ◽  
pp. 1340-1353 ◽  
Author(s):  
Yu Wu ◽  
Ning Hu ◽  
Xiangju Qu
Keyword(s):  
Optimization Algorithm ◽  
Trajectory Optimization ◽  
Fitness Function ◽  
Control Variable ◽  
Optimization Method ◽  
Operation Efficiency ◽  
Ground Motion Model ◽  
Aircraft System ◽  
Chicken Swarm Optimization ◽  
Flight Deck

Enhancing operation efficiency of flight deck has become a hotspot because it has an important impact on the fighting capacity of the carrier–aircraft system. To improve the operation efficiency, aircraft need taxi to the destination on deck with the optimal trajectory. In this paper, a general method is proposed to solve the trajectory optimization problem for aircraft taxiing on flight deck considering that the existing methods can only deal with the problem in some specific cases. Firstly, the ground motion model of aircraft, the collision detection strategy and the constraints are included in the mathematical model. Then the principles of the chicken swarm optimization algorithm and the generality of the proposed method are explained. In the trajectory optimization algorithm, several strategies, i.e. generation of collocation points, transformation of control variable, and setting of segmented fitness function, are developed to meet the terminal constraints easier and make the search efficient. Three groups of experiments with different environments are conducted. Aircraft with different initial states can reach the targets with the minimum taxiing time, and the taxiing trajectories meet all the constraints. The reason why the general trajectory optimization method is validated in all kinds of situations is also explained.

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