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On merging sequencing and scheduling theory with genetic algorithms to solve stochastic job shops.
(1997)
The stochastic job shop problem was solved using two genetic algorithms. The first was a stochastic constrained genetic algorithm to minimize total tardiness and to evaluate chromosomes using probability Gantt charting. ...
Decomposition techniques for support vector machines training and applications.
(2002)
The theory of the Support Vector Machine (SVM) algorithm is based on statistical learning theory and can be applied to pattern recognition and regression. Training of SVMs leads to either a quadratic programming (QP) ...