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Developing VRP models improves advanced solving methods based on mathematical programming, heuristics and meta-heuristics.
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We present mathematical programming based heuristics for finding classifiers with a small number of misclassifications on the design dataset with multiple classes.
These are based on stochastic models, mathematical programming models, heuristic techniques, and simulation.
The reliability design problems have been studied in the literature for decades, usually using mathematical programming or heuristic optimization approaches.
The reliability design optimization problem has been studied in the literature for decades, usually using mathematical programming or heuristic optimization approaches.
Numerous researchers have attempted to solve this problem with mathematical programming or heuristic methods, but all these methods share the significant weakness of low computational efficiency.
The presentation of mathematical programs and heuristics is commonly used to solve scheduling problems (Stafford et al. 2005).
Solution algorithms for TEP problems mainly fall into either mathematical programming classes or heuristic search classes.
In the past, mathematical programming and a general heuristics algorithm were used to solve globalized supply chain network design problems.
Cardoen et al., however, separate the methods into several broad categories, including mathematical programming, simulation and improvement heuristic [ 4].
A design is proposed which uses a variety of metaheuristic, heuristics and mathematical programming techniques within a hybrid framework.
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