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global optimization
Filled functions for unconstrained global optimization
      
The paper is concerned with the filled functions for global optimization of a continuous function of several variables.
      
To improve the efficiency of the branch-and-bound technique, some heuristic principles were proposed to cut those branches that may generate a global optimization solution with low probability.
      
On the basis of the inherent distribution within the immune response, the global optimization of the antibody was realized through parallel local optimization.
      
The possibility of using heat conductivity equation with a simple boundary layer for global optimization is investigated.
      
The use of Helmholtz (diffraction and diffusion) and heat conductivity equations for global optimization is described in Part I.
      
Cutting methods in En+ 1 for global optimization of a class of functions
      
Solution of the phase problem (reconstruction of the spectrum phase from the measured values of the spectrum amplitude) is considered from positions of global optimization.
      
The proposed method is a fusion of block-matching motion estimation and global optimization technique.
      
To avoid some contradictions between global optimization techniques and piece-wise smooth values of sought motion vectors, a hidden segmentation model is utilized.
      
We merge this "quantum" ideology with the philosophy of Particle Swarm Optimization to get the global optimization algorithm which can be called Quantum Swarm Optimization.
      
For a global optimization of both the yield and productivity, the optimum anthocyanin yield and productivity of 272 mg.L-11 and 30.2 mg.L-1d1 on day 9 were achieved by a two-stage culture with a temperature-shift from 30°C after 3 d to 20°C.
      
Genetic algorithms (GA) are a new type of global optimization methodology based on nature selection and heredity, and its power comes from the evolution process of the population of feasible solutions by using simple genetic operators.
      
Experimental results show that the proposed algorithm is an efficient global optimization algorithm.
      
The algorithm can realize global optimization and improve the search efficiency, and can be applied effectively in industrial optimization, data mining and pattern recognition.
      
A modified statistical iteration technique for the global optimization of multivariates in chromatographic separations
      
A computer approach to the global optimization of multivariates in chromatographic separations is presented using a modified statistical iteration technique, and the optimization of GLC separations is used as the example.
      
Artificial neural networks and multiple linear regression retention models in combination with several criteria functions were used and compared in global optimization process.
      
Analysis and improvement of TCP congestion control mechanism based on global optimization model
      
Network flow control is formulated as a global optimization problem of user profit.
      
 

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