Particle Swarm Optimization in Economics
AbstractParticle swarm optimization (PSO) is a population based stochastic optimization technique. PSO is similar to optimization with Genetic Algorithms (GA). In PSO, the potential solutions (particles) move through the problem space by following the current optimum particles. Experience shows that PSO is robust accross different families of optimization problems. We use PSO in some typical economic models where the problems of local extremum points are present, for example principal agent problems, and study the performance of PSO. We also compare the performance of PSO to the performance of other stochastic optimization techniques, for example simmulated annealing
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 444.
Date of creation: 04 Jul 2006
Date of revision:
Stochastic optimization; principal agent models;
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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