54,888 research outputs found
Firefly Algorithm, Stochastic Test Functions and Design Optimisation
Modern optimisation algorithms are often metaheuristic, and they are very
promising in solving NP-hard optimization problems. In this paper, we show how
to use the recently developed Firefly Algorithm to solve nonlinear design
problems. For the standard pressure vessel design optimisation, the optimal
solution found by FA is far better than the best solution obtained previously
in literature. In addition, we also propose a few new test functions with
either singularity or stochastic components but with known global optimality,
and thus they can be used to validate new optimisation algorithms. Possible
topics for further research are also discussed.Comment: 12 pages, 11 figure
Parallel Deterministic and Stochastic Global Minimization of Functions with Very Many Minima
The optimization of three problems with high dimensionality and many local minima are investigated
under five different optimization algorithms: DIRECT, simulated annealing, Spall’s SPSA algorithm, the KNITRO
package, and QNSTOP, a new algorithm developed at Indiana University
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