Optimisation of Production Strategies using Stochastic Search Methods

1996 ◽  
Author(s):  
P. R. King ◽  
T. J. Harding ◽  
N. J. Radcliffe
Keyword(s):  
Stochastic Search ◽  
Search Methods ◽  
Production Strategies

Optimisation of Production Strategies using Stochastic Search Methods

1996 ◽  
Author(s):  
T.J. Harding ◽  
N.J. Radcliffe ◽  
P.R. King
Keyword(s):  
Stochastic Search ◽  
Search Methods ◽  
Production Strategies

Stochastic Search Methods

1999 ◽  
pp. 299-350 ◽  
Author(s):  
Christian Jacob
Keyword(s):  
Stochastic Search ◽  
Search Methods

scholarly journals A note on stochastic search methods for global optimization

1988 ◽  
Vol 20 (02) ◽  
pp. 476-478 ◽  
Author(s):  
D. P. Kennedy
Keyword(s):  
Global Optimization ◽  
Beta Distribution ◽  
Golden Section ◽  
Stochastic Search ◽  
Limiting Distribution ◽  
Search Methods ◽  
Golden Section Search

Let [An, Bn ] be random subintervals of [0, 1] defined recursively as follows. Let A 1 = 0, B 1 = 1 and take Cn , D n to be the minimum and maximum of k, i.i.d. random points uniformly distributed on [An, Bn ]. Choose [An+1, Bn+ 1] to be [Cn , Bn ], [Any Dn ] or [Cn , Dn ] with probabilities p, q, r respectively, p + q + r = 1. It is shown that the limiting distribution of [Any Bn ] has the beta distribution on [0,1] with parameters k(p + r) and k(q + r). The result is used to consider a randomized version of Golden Section search.

scholarly journals EVOLUTIONARY ALORITHMS AT CHOICE: FROM GA TO GP

2015 ◽  
Vol 2 ◽  
pp. 185 ◽  
Author(s):  
Peter Grabusts
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Algorithms ◽  
Genetic Programming ◽  
Evolutionary Programming ◽  
Stochastic Search ◽  
Evolution Strategies ◽  
Natural Evolution ◽  
Search Methods ◽  
The World ◽  
Classification Tasks

Nowadays the possibilities of evolutionary algorithms are widely used in many optimization and classification tasks. Evolutionary algorithms are stochastic search methods that try to emulate Darwin’s principle of natural evolution. There are (at least) four paradigms in the world of evolutionary algorithms: evolutionary programming, evolution strategies, genetic algorithms and genetic programming. This paper analyzes present-day approaches of genetic algorithms and genetic programming and examines the possibilities of genetic programming that will be used in further research. The paper presents implementation examples that show the working principles of evolutionary algorithms.

scholarly journals Stochastic Search Methods for Mobile Manipulators

2018 ◽  
Vol 17 ◽  
pp. 976-984
Author(s):  
Amoako-Frimpong Samuel Yaw ◽  
Matthew Messina ◽  
Henry Medeiros ◽  
Jeremy Marvel ◽  
Roger Bostelman
Keyword(s):  
Stochastic Search ◽  
Mobile Manipulators ◽  
Search Methods
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