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Obtaining globally optimal solutions for optimization problems involve with DoCF is difficult and NP-hard [28].
Recently, many studies hybridize two or more algorithms to obtain optimal solutions for optimization problems [31].
These two algorithms are tested on several mathematical optimization functions to observe and confirm their effective behaviours in finding the optimal solutions for optimization problems.
GA is a population-based meta-heuristic algorithm using to find near-optimum solutions for optimization problems with complexity.
Consideration of all solutions for optimization of steam gathering scheme in Kamchatka's geothermal plants is believed not to be reasonable.
The physical annealing process is simulated in the simulated annealing (SA) technique for the determination of global or near-global optimum solutions for optimization problems.
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The extended model also introduces a new concept of efforts required in migration from a low HSI solution to a high HSI solution for optimization in BBO.
Here we describe a new technical solution for optimization of Pichia pastoris shake flask cultures with the example of production of stable human type II collagen.
Results show the ability of the proposed methodology to find better optimal solutions for structural optimization tasks than other optimization algorithms.
The quantitative analysis of various optimal value mappings and optimal solution mappings for optimization problems is an interesting and important topic in optimization theories and applications.
Results show the ability of the proposed methodology to find better solutions for structural optimization tasks as compared to other optimization algorithms.
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