PGSL

A direct stochastic algorithm for global search This paper presents a new algorithm called probabilistic global search lausanne (PGSL). PGSL is founded on the assumption that optimal solutions can be identified through focusing search around sets of good solutions. Tests on benchmark problems having multi-parameter nonlinear objective functions revealed that PGSL performs better than genetic algorithms and advanced algorithms for simulated annealing in 19 out of 23 cases studied. Furthermore as problem sizes increase, PGSL performs increasingly better than these other approaches. Empirical evidence of the convergence of PGSL is provided through its application to Lennard--Jones cluster optimisation problem. Finally, PGSL has already proved to be valuable for engineering tasks in areas of design, diagnosis and control.

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References in zbMATH (referenced in 11 articles , 1 standard article )

Showing results 1 to 11 of 11.
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  1. Ke, Jau-Chuan; Liu, Tzu-Hsin; Wu, Chia-Huang: An optimum approach of profit analysis on the machine repair system with heterogeneous repairmen (2015)
  2. Liu, Tzu-Hsin; Ke, Jau-Chuan: On the multi-server machine interference with modified Bernoulli vacation (2014)
  3. Wu, Chia-Huang; Lee, Wen-Chiung; Ke, Jau-Chuan; Liu, Tzu-Hsin: Optimization analysis of an unreliable multi-server queue with a controllable repair policy (2014)
  4. El Moumen, Samira; Ellaia, Rachid; Aboulaich, Rajae: A new hybrid method for solving global optimization problem (2011)
  5. Bel Hadj Ali, N.; Smith, I. F. C.: Dynamic behavior and vibration control of a tensegrity structure (2010)
  6. Rhode-Barbarigos, Landolf; Jain, Himanshu; Kripakaran, Prakash; Smith, Ian F. C.: Design of tensegrity structures using parametric analysis and stochastic search (2010) ioport
  7. Regis, Rommel G.; Shoemaker, Christine A.: Parallel stochastic global optimization using radial basis functions (2009)
  8. Esquível, Manuel L.: A conditional Gaussian martingale algorithm for global optimization (2006)
  9. Raphael, Benny; Smith, Ian F. C.: Global search through sampling using a PDF (2003)
  10. Raphael, B.; Smith, I. F. C.: A direct stochastic algorithm for global search (2003)
  11. Guimier, A.: Modélisation d’algorithmes d’optimisation à stratégie aléatoire. (Modelling random search optimization algorithms) (1986)