An improved particle swarm optimization model for solving homogeneous discounted series-parallel redundancy allocation problems

2017 ◽  
Vol 30 (3) ◽  
pp. 1175-1194 ◽  
Author(s):  
Seyed Mohsen Mousavi ◽  
Najmeh Alikar ◽  
Madjid Tavana ◽  
Debora Di Caprio
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Model ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Redundancy Allocation ◽  
Improved Particle Swarm Optimization ◽  
Allocation Problems

scholarly journals Optimization for the Redundancy Allocation Problem of Reliability Using an Improved Particle Swarm Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
H. Marouani
Keyword(s):  
Particle Swarm Optimization ◽  
System Reliability ◽  
Particle Swarm ◽  
Classical Particle ◽  
Particle Swarm Algorithm ◽  
Swarm Optimization ◽  
Redundancy Allocation ◽  
Improved Particle Swarm Optimization ◽  
Efficiency And Effectiveness ◽  
In Series

This paper presents an enhanced and improved particle swarm optimization (PSO) approach to overcome reliability-redundancy allocation problems in series, series-parallel, and complex systems. The problems mentioned above can be solved by increasing the overall system reliability and minimizing the system cost, weight, and volume. To achieve this with these nonlinear constraints, an approach is developed based on PSO. In particular, the inertia and acceleration coefficients of the classical particle swarm algorithm are improved by considering a normal distribution for the coefficients. The new expressions can enhance the global search ability in the initial stage, restrain premature convergence, and enable the algorithm to focus on the local fine search in the later stage, and this can enhance the perfection of the optimization process. Illustrative examples are provided as proof of the efficiency and effectiveness of the proposed approach. Results show that the overall system reliability is far better when compared with that of some approaches developed in previous studies for all three tested cases.

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