Verifiable outsourcing of constrained nonlinear programming by particle swarm optimization in cloud

2017 ◽  
Vol 22 (10) ◽  
pp. 3343-3355 ◽  
Author(s):  
Tao Xiang ◽  
Weimin Zhang ◽  
Shigang Zhong ◽  
Jiyun Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Nonlinear Programming ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Constrained Nonlinear Programming

Research on Site Selection of Aviation Overhaul Depot Based on Particle Swarm Optimization

2013 ◽  
Vol 274 ◽  
pp. 620-623
Author(s):  
Cheng Liang Liu ◽  
Hui Lin Fan ◽  
Man Yi Hou ◽  
Xue Liang Bao
Keyword(s):  
Particle Swarm Optimization ◽  
Nonlinear Programming ◽  
Support System ◽  
Site Selection ◽  
Particle Swarm ◽  
Mathematic Model ◽  
Swarm Optimization ◽  
Aviation Maintenance ◽  
Nonlinear Programming Method ◽  
Selection Of

As support agencies of the aviation maintenance and support system, the aviation overhaul depots undertake an important and arduous support mission, which play a pivotal role, so the science and rationality of site selection is extremely significant. This paper choose the nonlinear programming method to build a mathematic model, so as to solve the problem. For the purpose of optimizing and solving the model, a thought based on the improved particle swarm optimization which used in the model is put forward to, and an improved PSO which gained by the analyzing the standard PSO and improving the initial PSO is presented in this paper. Finally, an application example is given to analyze and summarize the model.

Design of Temperature Controllor in Diamond Synthetic Chamber Based on Multi-Objective Particle Swarm Optimization

2014 ◽  
Vol 496-500 ◽  
pp. 1448-1451
Author(s):  
Hong Yan Hua ◽  
Cheng Zhao
Keyword(s):  
Particle Swarm Optimization ◽  
Nonlinear Programming ◽  
Strong Convergence ◽  
Control Problem ◽  
Temperature Control ◽  
Particle Swarm ◽  
Nonlinear Programming Problem ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Simulation Results

Temperature control problem is a typical multi-constraint/multi-objective nonlinear programming problem in diamond synthetic chamber and it cannot be solved by conventional methods. This paper proposed a constraint multi-objective particle swarm optimization (CMOPSO) algorithm to solve the problem. Simulation results show that the CMOPSO algorithm can be used effectively in diamond temperature control and it has strong convergence optimization abilities for all different parameters and constraint conditions.

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