Introduction to operations research, 4th ed.
Introduction to operations research, 4th ed.
A linear approximation for redundant reliability problems with multiple component choices
Computers and Industrial Engineering
An efficient heuristic for series-parallel redundant reliability problems
Computers and Operations Research
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Adaptive particle swarm optimization: detection and response to dynamic systems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Multiobjective optimization using dynamic neighborhood particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Immune algorithms-based approach for redundant reliability problems with multiple component choices
Computers in Industry - Special issue: Application of genetics algorithms in industry
Penalty guided PSO for reliability design problems
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Particle evolutionary swarm for design reliability optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
Recent Advances in Optimal Reliability Allocation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On the computational complexity of reliability redundancy allocation in a series system
Operations Research Letters
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In this paper, the performance of a particle swarm optimization (PSO) algorithm named Annealing-based PSO (APSO) is investigated to solve the redundant reliability problem with multiple component choices (RRP-MCC). This problem aims to choose an optimal combination of components and redundancy levels for a system with a series-parallel configuration that maximizes the overall system reliability. PSO is a population-based meta-heuristic algorithm inspired by the social behavior of the biological swarms that is designed for continuous decision spaces. As a local search engine (LSE), the proposed APSO employs the Metropolis-Hastings strategy, the key idea behind the simulated annealing (SA) algorithm. In APSO, the best position among all particles in each iteration is dynamically improved using the inner loop of the SA (i.e., equilibrium loop) while the temperature is updated in the main loop of the PSO algorithm. The well-known benchmarks are used to verify the performance of the proposed APSO. Even though APSO fails to outperform the best solution obtained in the literature, the contribution of this paper is comprised of the implementation of APSO as a hybrid meta-heuristic as well as the effect of Metropolis-Hastings strategy on the performance of the classical PSO.