PARTICLE SWARM OPTIMIZATION ALGORITHM BASED ON THE IDEA OF SIMULATED ANNEALING AND ITS CONVERGENCE
Particle Swarm Optimization (PSO) is an optimization’s algorithm based on swarm intelligence. PSO is an algorithm for global optimization, but PSO often trapped in the local best point. Otherwise, the acceptance rule by Metropolis, known as the Metropolis rule, in Simulated Annealing is known use...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/18216 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Particle Swarm Optimization (PSO) is an optimization’s algorithm based on swarm intelligence. PSO is an algorithm for global optimization, but PSO often trapped in the local best point. Otherwise, the acceptance rule by Metropolis, known as the Metropolis rule, in Simulated Annealing is known useful to get out of the local <br />
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best point. To overcome this problem, PSO is modified with the acceptance rule by Metropolis. The modified is called Simulated Annealing Particle Swarm Optimization (SAPSO). |
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