Computational economics and finance: modeling and analysis with Mathematica
Computational economics and finance: modeling and analysis with Mathematica
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
| Hi-index | 0.00 |
The thesis of this study is that the use of discrete simulations is the most appropriate instrument to support the definition of any organs allocation procedure. We studied the influence of recipient pool size on the probability of obtaining a good match grade and the exchange rate between regional and/or interregional organizations for two different hypothesis of national allocation schemes. We also showed the potential of simulation methods at assessing the most appropriate adjustments for the optimization of any allocation scheme.