Heat transfer and fluid flow for tube included a porous media: Assessment and Multi-Objective Optimization Using Particle Swarm Optimization (PSO) Algorithm

2020 ◽  
Vol 545 ◽  
pp. 123804 ◽  
Author(s):  
Sajjad Keykhah ◽  
Ehsanolah Assareh ◽  
Rahim Moltames ◽  
Mohsen Izadi ◽  
Hafiz Muhammad Ali
Keyword(s):  
Heat Transfer ◽  
Porous Media ◽  
Particle Swarm Optimization ◽  
Fluid Flow ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective

scholarly journals A Multi-objective Particle Swarm Optimization Based on P System Theory

2018 ◽  
Vol 232 ◽  
pp. 03039
Author(s):  
Taowei Chen ◽  
Yiming Yu ◽  
Kun Zhao
Keyword(s):  
Particle Swarm Optimization ◽  
Pareto Front ◽  
Search Strategy ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
P System ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective

Particle swarm optimization(PSO) algorithm has been widely applied in solving multi-objective optimization problems(MOPs) since it was proposed. However, PSO algorithms updated the velocity of each particle using a single search strategy, which may be difficult to obtain approximate Pareto front for complex MOPs. In this paper, inspired by the theory of P system, a multi-objective particle swarm optimization (PSO) algorithm based on the framework of membrane system(PMOPSO) is proposed to solve MOPs. According to the hierarchical structure, objects and rules of P system, the PSO approach is used in elementary membranes to execute multiple search strategy. And non-dominated sorting and crowding distance is used in skin membrane for improving speed of convergence and maintaining population diversity by evolutionary rules. Compared with other multi-objective optimization algorithm including MOPSO, dMOPSO, SMPSO, MMOPSO, MOEA/D, SPEA2, PESA2, NSGAII on a benchmark series function, the experimental results indicate that the proposed algorithm is not only feasible and effective but also have a better convergence to true Pareto front.

Application of Particle Swarm Optimization in Cylinder Helical HGearH Multi-Objective Design

2011 ◽  
Vol 474-476 ◽  
pp. 2229-2233
Author(s):  
Yuan Bin Mo ◽  
Ji Zhong Liu ◽  
Bao Lei Wang ◽  
Wei Min Wan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Design ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective

Cylinder helical gGear is widely used in industry. Multi-objective optimization design of the component is often met in its different application sSituation. In this paper a novel multi-objective optimization method based on Particle Swarm Optimization (PSO) algorithm is designed for applying to solve this kind of problem. A paradigm depicted in the paper shows the algorithm is practical.

Particle Swarm Optimization for Cylinder Helical Gear Multi-Objective Design Problems

2011 ◽  
Vol 109 ◽  
pp. 216-221
Author(s):  
Yuan Bin Mo
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Weighted Average ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Helical Gear ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Gear Design

The models for many problems in cylinder helical gear design are all multi-objective optimization. But there isn’t an effective algorithm for solving multi-objective optimization, and now the only method for it is changing multi-objective into one objective by weighted average. In this paper a novel multi-objective optimization method based on Particle Swarm Optimization (PSO) algorithm is designed for applying to solve this kind of problem. A paradigm depicted in the paper shows the algorithm is practical.

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