Abstract: Two-echelon vehicle routing problem (2E-VRP) is an NP-hard combinatorial optimization problem and a basic mathematical model of modern city ... an embedded Hamiltonian graph-guided heuristic ...

our benchmarking method can be used to compare stochastic optimization algorithms by graphs. Compared with traditional benchmarking methods, our method is synthetic statistically and therefore is ...

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In order to ensure the prediction accuracy of mechanical properties, a TCMSSA-ELM model, which is a hybrid of the ... convergence when dealing with large-scale problems [42]. GA is an evolutionary ...

learn the math behind policies, and experiment with real-world applications! 🔥💡 Deep Reinforcement Learning in Rust is a modular framework implementing key reinforcement learning algorithms in the ...

Google's artificial intelligence (AI) research lab DeepMind has unveiled an advanced agent, AlphaEvolve, which can target fundamental and complex mathematics and computing problems. It has the ...

AlphaProof combines language models with ... two combinatorics problems, showing remaining limitations. The achievement comes as AI researchers increasingly use math competitions to benchmark ...

Most AI models ... as algorithms, making it a poor fit for problems that aren’t numerical. To benchmark AlphaEvolve, DeepMind had the system attempt a curated set of around 50 math problems ...

Google's DeepMind research division claims its newest AI agent marks a significant step toward using the technology to tackle big problems in math and ... large language models (LLMs), with ...

AlphaEvolve pairs Google’s Gemini large language models ... mathematics,” explained Matej Balog, a researcher at Google DeepMind, in an interview with VentureBeat. “It can discover ...

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