However, knowledge about what makes the solutions optimal can be more valuable as it can be formulated as heuristics for guiding future designs of similar systems. In this paper, we propose a methodology that c
Tree search hyper-heuristic with application to combinatorial optimization Francisco Javier Gil-Gala Marko Ɖurasevic Ramiro Varela OriginalPaperOpen access17 May 2025Article: 25 A biased-randomised iterated local search for the team orienteering arc routing problem allowing different origin and destination...
Procedia Computer ScienceF. Alsolami, I. Chikalov, and M. Moshkov, "Comparison of heuristics for in- hibitory rule optimization," in 18th International Conference in Knowledge Based and Intelligent Information and Engineering Systems, KES 2014, 2014, pp. 378-387....
Further elu- cidation of human strategiesand heuristics for optimization problems such as the E-TSP will aid our un- derstanding of how cognitive processes have adapted to the demands of combinatorial difficulty. In the everyday world, the capacity of human beings to make optimal decisions may ...
machine-learningdeep-reinforcement-learningheuristicsoperations-researchtravelling-salesman-problem UpdatedNov 7, 2022 Jupyter Notebook optframe/optframe Star83 Code Issues Pull requests OptFrame - C++17 (and C++20) Optimization Framework in Single or Multi-Objective. Supports classic metaheuristics and hype...
Introduction_Of_Convex_Optimization starting poing for a local optimization method, applied to the original nonconvex problem. 4.2 Convex heuristics...for nonconvex optimization \qquadConvex optimization is the basis for several heuristics for solving...While this is a difficult combinatorial problem, ...
The Journal of Heuristics provides a forum for advancing the state-of-the-art in the theory and practical application of techniques for solving problems approximately that cannot be solved exactly. It fosters the development, understanding, and practical use of heuristic solution techniques for solving...
aphysics prior forDeepLearningandapplies the resulting network topology for model-based..., Non-convex optimization, Theory TL;DR:Efficient dictionarylearningbyL1minimization viaanovel 模型压缩备用 /compact convolutional filtersknowledgedistillationAchieving compactingandaccelerating CNNs model... acceleratingdee...
Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ensembles have been examined in the literature, e.g., random feature selection, weak
“intelligent manufacturing”, “manufacturing scheduling”, “shop scheduling”, “meta-heuristic”, “evolutionary algorithm”, “intelligent optimization”, “reinforcement learning”, “Q-learning”, “state-action-reward-state-action (SARSA)” and their combinations as index keywords in Web of ...