Developing Interval Global Optimization Algorithms on the Basis of Branch-and-Bound and Constraint Propagation Methods

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.

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The Challenge for the Nature-inspired Global Optimization Algorithms: Non-symmetric Benchmark Functions

IEEE Access ◽

10.1109/access.2021.3100365 ◽

2021 ◽

pp. 1-1

Author(s):

Zheng-Ming Gao ◽

Juan Zhao ◽

Yu-Rong Hu ◽

Hua-Feng Chen

Keyword(s):

Global Optimization ◽

Optimization Algorithms

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

Informatization and communication ◽

10.34219/2078-8320-2021-12-1-113-117 ◽

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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A Global Optimization Algorithm for Sum of Linear Ratios Problem

Journal of Applied Mathematics ◽

10.1155/2013/276245 ◽

2013 ◽

Vol 2013 ◽

pp. 1-7 ◽

Cited By ~ 7

Author(s):

Yuelin Gao ◽

Siqiao Jin

Keyword(s):

Global Optimization ◽

Lower Bound ◽

Programming Problem ◽

Branch And Bound ◽

Numerical Experiments ◽

Original Problem ◽

Bilinear Programming ◽

Global Optimization Algorithm ◽

Product Function ◽

Optimal Value

We equivalently transform the sum of linear ratios programming problem into bilinear programming problem, then by using the linear characteristics of convex envelope and concave envelope of double variables product function, linear relaxation programming of the bilinear programming problem is given, which can determine the lower bound of the optimal value of original problem. Therefore, a branch and bound algorithm for solving sum of linear ratios programming problem is put forward, and the convergence of the algorithm is proved. Numerical experiments are reported to show the effectiveness of the proposed algorithm.

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