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Particle Swarm Optimization in Economics

Author

Listed:
  • Mico Mrkaic

    (University of Maribor)

Abstract

Particle 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

Suggested Citation

  • Mico Mrkaic, 2006. "Particle Swarm Optimization in Economics," Computing in Economics and Finance 2006 444, Society for Computational Economics.
    • Handle: RePEc:sce:scecfa:444
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    More about this item

    Keywords

    Stochastic optimization; principal agent models;

    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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