scholarly journals On estimating workload in interval branch-and-bound global optimization algorithms

2011 ◽  
Vol 56 (3) ◽  
pp. 821-844 ◽  
Author(s):  
José L. Berenguel ◽  
L. G. Casado ◽  
I. García ◽  
Eligius M. T. Hendrix
Keyword(s):  
Global Optimization ◽  
Branch And Bound ◽  
Optimization Algorithms ◽  
Interval Branch And Bound

scholarly journals TEMPLATE REALIZATION OF GENERALIZED BRANCH AND BOUND ALGORITHM

2005 ◽  
Vol 10 (3) ◽  
pp. 217-236 ◽  
Author(s):  
M. Baravykaite ◽  
R. Čiegis ◽  
J. Žilinskas
Keyword(s):  
Global Optimization ◽  
Combinatorial Optimization ◽  
Branch And Bound ◽  
Optimization Algorithms ◽  
Optimization Methods ◽  
Branch And Bound Algorithm ◽  
Computational Experiments ◽  
Branch And Bound Algorithms ◽  
Parallel Branch And Bound

In this work we consider a template for implementation of parallel branch and bound algorithms. The main aim of this package to ease implementation of covering and combinatorial optimization methods for global optimization. Standard parts of global optimization algorithms are implemented in the package and only method specific rules should be implemented by the user. The parallelization part of the tool is described in details. Results of computational experiments are presented and discussed. Straipsnyje pristatyta apibendrinto šaku ir režiu algoritmo šablono realizacija. Irankis skirtas palengvinti nuosekliuju ir lygiagrečiuju optimizacijos uždaviniu programu kūrima. Nuo uždavinio nepriklausančios algoritmo dalys yra idiegtos šablone ir vartotojui reikia sukurti tik nuo uždavinio priklausančiu daliu realizacija. Šablone idiegti keli lygiagretieji algoritmai, paremti tyrimo srities padalinimu tarp procesoriu. Pateikiami skaičiavimo eksperimentu rezultatai.

On hybridization of stochastic global optimization algorithms taking into account the features of their architecture

2021 ◽  
Vol 1 ◽  
pp. 113-117
Author(s):  
Dmitry Syedin ◽  
Keyword(s):  
Global Optimization ◽  
Stochastic Optimization ◽  
Optimization Algorithms ◽  
Stochastic Global Optimization ◽  
Stochastic Optimization Algorithms ◽  
Pca Algorithm

The work is devoted to the hybridization of stochastic global optimization algorithms depending on their architecture. The main methods of hybridization of stochastic optimization algorithms are listed. An example of hybridization of the algorithm is given, the modification of which became possible due to taking into account the characteristic architecture of the M-PCA algorithm.

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