scholarly journals Hybrid Particle Swarm Optimization Algorithm for Process Planning

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1745
Author(s):  
Xu Zhang ◽  
Pan Guo ◽  
Hua Zhang ◽  
Jin Yao
Keyword(s):  
Particle Swarm Optimization ◽  
Process Planning ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Genetic Operators ◽  
Swarm Optimization ◽  
Hybrid Particle ◽  
Hierarchical Coding ◽  
Hybrid Particle Swarm Optimization

Process planning is a typical combinatorial optimization problem. When the scale of the problem increases, combinatorial explosion occurs, which makes it difficult for traditional precise algorithms to solve the problem. A hybrid particle swarm optimization (HPSO) algorithm is proposed in this paper to solve problems of process planning. A hierarchical coding method including operation layer, machine layer and logic layer is designed in this algorithm. Each layer of coding corresponds to the decision of a sub-problem of process planning. Several genetic operators of the genetic algorithm are designed to replace the update formula of particle position and velocity in the particle swarm optimization algorithm. The results of the benchmark example in case study show that the algorithm proposed in this paper has better performance.

Optimal design of adaptive and proportional integral derivative controllers using a novel hybrid particle swarm optimization algorithm

2020 ◽  
Vol 42 (8) ◽  
pp. 1492-1510
Author(s):  
Elham Yazdani Bejarbaneh ◽  
Arash Hosseinian Ahangarnejad ◽  
Ahmad Bagheri ◽  
Behnam Yazdani Bejarbaneh ◽  
Binh Thai Pham ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Inverted Pendulum ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Pendulum System ◽  
Hybrid Particle ◽  
Inverted Pendulum System ◽  
Hybrid Particle Swarm Optimization

Controlling of a rotational inverted pendulum is considered as a challenging problem, mainly due to the system’s inherent nonlinear and unstable dynamics. In fact, the goal of this control is to maintain the pendulum vertically upward regardless of external disturbances. This paper aims to optimally design a model reference adaptive proportional integral derivative (PID) control for rotary inverted pendulum system based on a novel hybrid particle swarm optimization algorithm, combining sine cosine algorithm and levy flight distribution. Evaluation of the performance quality of the proposed adaptive controller is accomplished based on the stabilization and tracking control of rotary inverted pendulum system. In addition, two other PID controllers are designed to get a better understanding of the performance and robustness of the proposed controller. To make a complete comparison, the performance of the hybrid particle swarm optimization algorithm is examined against two other optimization techniques known as simple particle swarm optimization and whale optimization algorithm. Finally, the obtained simulation results demonstrate that the proposed optimal adaptive controller is superior to the other controllers, especially in terms of the transient response characteristics and the magnitude of control output signal.

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