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

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鼓掌

A Hierarchical Cooperative Coevolutionary Approach to?Solve Very Large-Scale Traveling Salesman ProbP. In the numerical experiments, we design two strategies: (1). Random decomposition. (2). Decomposition based on the greedy solution. 10 symmetric instances of VLSTSP ranging from 38,478 to 238,025 are employed to evaluate our proposal, and the basic optimizer is greedy Local Search (gLS). Experime

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Tornado: An Autonomous Chaotic Algorithm for?High Dimensional Global Optimization Problemsroposed Tornado algorithm is an effective and efficient optimization algorithm..A panel of various benchmark problems with different properties was used to assess the performance of the proposed chaotic algorithm. The obtained results have shown the scalability of the algorithm in contrast to chaoti

陳腐思想

Mixing Data Augmentation Methods for?Semantic Segmentation the benefits of combining mixing strategies with traditional data augmentation techniques; namely an improvement of almost 5% was achieved using these methods regarding models trained only with traditional data augmentation methods.

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We Won’t Get Fooled Again: When Performance Metric Malfunction Affects the?Landscape of?Hyperparametthese cases, a worsened correlation between the observed fitness and average fitness in the neighborhood is observed, potentially making harder the deployment of local-search-based HPO strategies. (iii) these effects are observed across different HPO scenarios (tuning CNN or XGBoost algorithms). Fin