We are very happy to announce that CPLEX Optimization Studio 12.10 was released last Friday, with callbacks in CP Optimizer, branching context in the new CPLEX Generic callback framework, and much performance improvements.
CPLEX is proud to announce that in the newest release, version 12.10, for the first time, a commercial Mathematical Optimization solver implements a Machine-Learning-based classifier to make automatic decisions over some algorithmic choices. Using this classifier, the solution time decreases by 28% for the whole validation set and 49% for models in the validation set that take at least 1 second to solve.
The upcoming CPLEX release features multiobjective optimization. Available for LPs and MIPs, it allows to specify combinations of hierarchical and blended objectives, and gives you an optimal solution for your instance. Thanks to tolerances on each sub-objective, you can evaluate the impact that each objective has on the others. And the weights on each objective allow to scale each objective, either for trade-off exploration, or to help numerical stability.
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