Titlebook: Learning and Intelligent Optimization; 10th International C Paola Festa,Meinolf Sellmann,Joaquin Vanschoren Conference proceedings 2016 Spr

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Teck-Hou Teng,Stephanus Daniel Handoko,Hoong Chuin Lau

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Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solversier to solve for one solver and much harder to solve for the other. This instance set offers the potential to identify key features which allow to distinguish between the problem hardness classes of both algorithms.

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Parallelizing Constraint Solvers for Hard RCPSP Instancesgths of different constraint solvers Our approach seeks to predict and run in parallel the best solvers for a new, unseen RCPSP instance by enabling the bound communication between them. This on-average allows to outperform the oracle solver that always chooses the best available solver for any given instance.

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