A distributed parallel genetic algorithm for solving optimal growth models

DOI10.1007/BF01298458zbMath0840.90028MaRDI QIDQ1906175

Paul M. Beaumont, Patrick T. Bradshaw

Publication date: 8 February 1996

Published in: Computational Economics (Search for Journal in Brave)

zbMATH Keywords

distributed parallel genetic algorithmmultiple state problemssingle state deterministic optimal growth model

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Economic growth models (91B62)

Related Items (8)

Designing a superstructure for parametric search for optimal search spaces in non‐trivial optimization problems ⋮ Functional search in economics using genetic programming ⋮ A multipurpose parallel genetic hybrid algorithm for nonlinear nonconvex programming problems ⋮ A parallel implementation of the simplex function minimization routine ⋮ Multi-core CPUs, clusters, and grid computing: A tutorial ⋮ Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm ⋮ Concurrent processing of mixed‐integer non‐linear programming problems ⋮ Scalability of the genetic hybrid algorithm on a parallel supercomputer

Uses Software

• PVM

Cites Work

• The parallel genetic algorithm as function optimizer
• Projection methods for solving aggregate growth models
• Discrete-Time Finite Horizon Approximation of Infinite Horizon Optimization Problems with Steady-State Invariance
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