Sentence examples for optimization knowledge from inspiring English sources

In this paper, a knowledge-based modeling approach, PAM (disruption-handling Policies, local search Algorithms and object-oriented Modeling), is developed, which combines the scheduling knowledge of experienced schedulers with the optimization knowledge concerning models and algorithms in the field of Operations Research to obtain an effective solution in real time.

The inductor optimization requires knowledge of such parameters at a few representative frequencies.

The technique robustly identifies optimal weighted random sampling schemes and provides improved reconstruction fidelity for multiple 1D and 2D images, when compared to prior techniques for sampling optimization given knowledge of the image geometry.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System.

> -wrap-foot> True optimization requires knowledge of the probabilities we want to estimate, which is obviously circular.

Analysis of coherence indicated an increasing common trend for enhancing the engagement of developing country stakeholders, building research capacity and optimization of knowledge management platforms in support of improved access to healthcare.

Future studies are needed, to explore whether personalization of format and the level of detail of content (particularly relating to numerical data) of P-DAs to users' preferences may enable optimization of knowledge translation outcomes, or at least be non-inferior to current methods, but potentially preferred by some users.

Besides manual optimization and knowledge-based methods, optimization metaheuristics such as Genetic Algorithms, Ant Colony Optimization and Particle Swarm Optimization have yielded outstanding results for the ICFMO.

Estimating an optimal set of parameters by optimization algorithms requires knowledge of the sensitivity of the process of interest to model parameters.

Firstly, a framework of robust optimization based on knowledge discovery from simulation is proposed.

(I, II) Theory and algorithms of analysis and design of hybrid systems, nonlinear and robust control, non-convex and convex optimization, formalization of knowledge in education, functional analysis and operator theory.