Sentence examples for advanced optimization techniques from inspiring English sources

The proposed work details the advanced optimization techniques used for product and process design integrating environmental concerns.

More specifically, a stochastic mixed integer linear programming model (MILP) has been developed, combining advanced optimization techniques with Monte Carlo method in order to deal with uncertainty issues.

We conclude that substantial improvements can be achieved in both accuracy and robustness of the correlations by using advanced optimization techniques.

There are more sophisticated algorithms like SWIPE [16, 17] that can produce a smaller overall detection lag upon processing a full audio signal and uses varying segment sizes as well as advanced optimization techniques.

Many games can be solved by just comparing these utility values across rows and columns; however this game is a little more complicated and requires advanced optimization techniques.

This is achieved by advanced optimization techniques such as genetic algorithms, which, however, are computationally intensive (Kostka et al., 2004), as they require checking all of the possible subnetworks to identify the ones that are most dysregulated.

Hence, the proposed extended model of BBO presents an advanced optimization technique that was originally proposed by Dan Simon as BBO in December, 2008.

It should be emphasized on the other hand that no advanced optimization technique is required for the derivation of the Theorem, provided the procedure in the Appendix just consists in transforming Problem 2 into another program where we do not have to deal directly with constraint (10) above.

This paper has presented the operational problem of blood sample collection faced by two large laboratories, and used an advanced optimization technique to solve it.

This can be achieved by a combination of traditional chemical process design methods, measurements of environmental impacts and advanced mathematical optimization techniques.

The key point of this strategy is the integration of preliminary design methods based on mean-line and throughflow models with the most advanced shape optimization techniques exploiting Computational Fluid-Dynamics (CFD).