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A Distributed Parallel Genetic Algorithm for Solving Optimal Growth Models

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  • Beaumont, Paul M
  • Bradshaw, Patrick T

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Bibliographic Info

Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 8 (1995)
Issue (Month): 3 (August)
Pages: 159-79

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Handle: RePEc:kap:compec:v:8:y:1995:i:3:p:159-79

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Cited by:
  1. Paul McNelis & John Duffy, 1998. "Approximating and Simulating the Stochastic Growth Model: Parameterized Expectations, Neural Networks, and the Genetic Algorithm," GE, Growth, Math methods 9804004, EconWPA, revised 04 May 1998.
  2. William L. Goffe & Michael Creel, 2005. "Multi-core CPUs, Clusters and Grid Computing: a Tutorial," Computing in Economics and Finance 2005 438, Society for Computational Economics.
  3. Ostermark, Ralf, 2004. "A multipurpose parallel genetic hybrid algorithm for non-linear non-convex programming problems," European Journal of Operational Research, Elsevier, vol. 152(1), pages 195-214, January.
  4. Kyle Klein & Julian Neira, 2014. "Nelder-Mead Simplex Optimization Routine for Large-Scale Problems: A Distributed Memory Implementation," Computational Economics, Society for Computational Economics, vol. 43(4), pages 447-461, April.
  5. Clemens, Christiane & Riechmann, Thomas, 1996. "Evolutionäre Optimierungsverfahren und ihr Einsatz in der ökonomischen Forschung," Hannover Economic Papers (HEP) dp-195, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  6. Donghoon Lee & Matthew Wiswall, 2007. "A Parallel Implementation of the Simplex Function Minimization Routine," Computational Economics, Society for Computational Economics, vol. 30(2), pages 171-187, September.
  7. Beaumont, Paul M. & Walker, Robert T., 1996. "Land degradation and property regimes," Ecological Economics, Elsevier, vol. 18(1), pages 55-66, July.

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