Titlebook: Learning and Intelligent Optimization; 12th International C Roberto Battiti,Mauro Brunato,Panos M. Pardalos Conference proceedings 2019 Spr

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Creating a Multi-iterative-Priority-Rule for the Job Shop Scheduling Problem with Focus on Tardy Jol paths is used to solve the static problem as a benchmark. The results show that all types provide better results than classical PR and that with and without time limit the types from best to worst are: MIPR, MPR, IPR, and PR. The gaps to the metaheuristic are also reported.

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How , Can Be Helpful to Iteratively Compute Negative Curvature Directions,can enhance the performance of the CG, allowing the computation of negative curvature directions, too. The overall method in our proposal significantly generalizes the theory proposed for [.] and [.], and straightforwardly allows the use of a CG-based method on indefinite Newton’s equations.

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Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Probof problem instances shows the effectiveness of the approach in comparison to a well-known mutation operator in terms of convergence speed and approximation quality. In addition, we glance at the neighbourhood structure and similarity of obtained Pareto-optimal solutions and derive promising directions for future work.

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0302-9743 mization, machine learning, and artificial intelligence. Special focus is given to advanced ideas, technologies, methods, and applications in optimization and machine learning..978-3-030-05347-5978-3-030-05348-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

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An Effective Heuristic for a Single-Machine Scheduling Problem with Family Setups and Resource Consr an extensive computational experience on benchmark of instances from the literature and randomly generated in this work. Results show that the developed heuristic significantly outperforms a state-of-the-art heuristic in terms of solution quality.

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