Titlebook: Optimization and Learning; 6th International Co Bernabé Dorronsoro,Francisco Chicano,El-Ghazali Ta Conference proceedings 2023 The Editor(s

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Algorithm Selection for Large-Scale Multi-objective Optimization Selection has known to benefit from the strengths on multiple algorithm rather than relying one. This trait offers performance gain with limited or no contribution on the algorithm and instance side. As the target application domain, Multi-objective Optimization is a realistic way of approaching an

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Solving the Nurse Scheduling Problem Using the Whale Optimization Algorithmd regularly in transportation, manufacturing, retail stores, academic institutions, and health care units. For the latter, healthcare personnel must be assigned required shifts to satisfy hospital requirements, while optimizing costs and quality of service. In this context, we propose a nature-inspi

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A Hierarchical Cooperative Coevolutionary Approach to Solve Very Large-Scale Traveling Salesman Prob. Due to the existence of the curse of dimensionality, it is difficult to find an acceptable solution for VLSTSP with conventional Evolutionary Algorithms (EAs). Cooperative Coevolution (CC) framework, which divides the problems into multiple subcomponents and optimizes them independently, offers a

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Tornado: An Autonomous Chaotic Algorithm for High Dimensional Global Optimization Problemsm introduces advanced symmetrization, levelling and fine search strategies for an efficient and effective exploration of the search space and exploitation of the best found solutions. To our knowledge, this is the first accurate and fast autonomous chaotic algorithm solving large scale optimization

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Mixing Data Augmentation Methods for Semantic Segmentationamount of images that might be difficult to obtain. This issue can be faced by means of data augmentation techniques that generate new images by applying geometric or colour transformations, or more recently by mixing several images using techniques such as CutMix or CarveMix. Unfortunately, mixing

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Real-Time Elastic Partial Shape Matching Using a Neural Network-Based Adjoint Methodrtial surface matching of non-linear deformable bodies is crucial in engineering to govern structure deformations. In this article, we propose to formulate the registration problem as an optimal control problem using an artificial neural network where the unknown is the surface force distribution th

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