A Routing Optimization Method for Software-Defined SGIN Based on Deep Reinforcement Learning

2019 ◽  
Author(s):  
Zhe Tu ◽  
Huachun Zhou ◽  
Kun Li ◽  
Guanglei Li ◽  
Qi Shen
Keyword(s):  
Reinforcement Learning ◽  
Optimization Method ◽  
Routing Optimization

APPLICATION OF NOVEL REINFORCEMENT LEARNING AUTOMATA APPROACH IN POWER SYSTEM REGULATION

2009 ◽  
Vol 18 (08) ◽  
pp. 1609-1625 ◽  
Author(s):  
MOHAMMAD KASHKI ◽  
YOUSSEF L. ABDEL-MAGID ◽  
MOHAMMAD A. ABIDO
Keyword(s):  
Reinforcement Learning ◽  
Pid Controller ◽  
Controller Design ◽  
Learning Automata ◽  
Synchronous Generator ◽  
Optimization Method ◽  
Avr System ◽  
Pid Controller Design ◽  
Analytical System ◽  
Reinforcement Learning Automata

In this paper, a novel efficient optimization method based on reinforcement learning automata (RLA) for optimum parameters setting of conventional proportional-integral-derivative (PID) controller for AVR system of power synchronous generator is proposed. The proposed method is Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) which is able to explore and learn to improve control performance without the knowledge of the analytical system model. This paper demonstrates the full details of the CDCARLA technique and compares its performance with Particle Swarm Optimization (PSO) as an efficient evolutionary optimization method. The proposed method has been applied to PID controller design. The simulation results show the superior efficiency and robustness of the proposed method.

Logistics Distribution Vehicle Routing Problem with Time Windows

2012 ◽  
Vol 468-471 ◽  
pp. 2047-2051 ◽  
Author(s):  
Ai Ling Chen
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Optimization Method ◽  
Hybrid Optimization ◽  
Local Optimum ◽  
Routing Problem ◽  
Logistics Distribution ◽  
Routing Optimization ◽  
Hybrid Optimization Method

Vehicle routing optimization problem is one of the major research topics in logistics distribution field. Suitable vehicle routing selection is vital to reduce the logistics cost. The paper presents a hybrid optimization method to solve the vehicle routing problem with time windows. In the hybrid optimization method, discrete particle swarm optimization algorithm is used to assign the customers on routes and simulated annealing (SA) algorithm to avoid becoming trapped in local optimum. The simulation results have shown that the proposed method is feasible and effective for the vehicle routing problem with time windows.

Agricultural Optimization of Cold-Chain Logistics Distribution Routing Based on PSO

2013 ◽  
Vol 756-759 ◽  
pp. 3941-3945 ◽  
Author(s):  
Wei Yang ◽  
Qian Zhang ◽  
Guo Dong Li
Keyword(s):  
Optimization Problem ◽  
Particle Swarm Optimization Algorithm ◽  
Optimization Method ◽  
Agricultural Products ◽  
Path Optimization ◽  
Cold Chain ◽  
Swarm Optimization ◽  
Logistics Distribution ◽  
Routing Optimization ◽  
Definition Of

The definition of the cold chain logistics and the problem of the agricultural cold chain logistics are introduced. According to the characteristics of cold chain logistics, exploring the cold chain logistics distribution path optimization method. Based on the model of the agricultural products cold chain logistics distribution routing optimization, particle swarm optimization algorithm is constructed to solve the optimization problem. Taking an example, the results have been conducted finally to demonstrate the effectiveness of the algorithm for agricultural products cold chain logistics distribution routing optimization problem.

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