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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. ...
Estimation of production cost variance using chronological simulation.
(1997)
Production costs are usually simulated on the basis that the availability of generation capacity is subject to random failures of system generating units. In order to estimate the variance of cost, both the random forced ...
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) ...
A mean-variance model for stochastic time-dependent networks.
(2005)
Traditional models of route generation are based on choosing routes that minimize expected travel-time between origin and destination. The variance of the least-time path is not included in the path selection. In addition, ...
Assembly job shop scheduling problems with component availability constraints.
(2007)
Job shop scheduling has been widely studied for several decades. In generalized of the job shop scheduling problem, n jobs are to be processed on m machines under specific routings and due dates. The majority of job shop ...
Dynamic optimization of service part inventory control policy through applied data mining and simulation.
(2007)
This research defines a novel approach for associating inventory item behavior, focusing initially on demand patterns, with an optimal inventory control policy. This method relies upon the definition of typical service ...
Optimization issues in data analysis: An analytic center approach to kernel methods.
(2001)
Support vector machines have recently attracted much attention in the machine learning and optimization communities for their remarkable generalization ability. The support vector machine solution corresponds to the center ...
An intelligent search-based methodology for selection of sample points for form error estimation.
(2002)
Efficient part feature verification through CMM requires prudent sampling of data points. This dissertation presents an adaptive sampling procedure, which uses manufacturing error patterns and optimization search methods ...
Multicriteria plant layout with evaluation by simulation.
(1997)
Another significant contribution of this research is that the layouts generated from this procedure are quickly incorporated into a simulation model which is used for evaluating layouts. Simulation offers a rich evaluation ...
Differential-algebraic equations in primal dual interior point optimization methods: A new approach to the parameterization of the central trajectory.
(2003)
Interior Point Methods (IPMs) are iterative algorithms for mathematical optimization problems that can be interpreted as path-following procedures. Given a starting solution, the iterative scheme generates a sequence of ...