Fruchter, G. (2026) Opportunism in Supply Chain Recommendations: A Dynamic Optimization Approach. Modern Economy, 17, 26-38.
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How DeepSeek’s new training method could disrupt advanced AI again
DeepSeek’s latest training research arrives at a moment when the cost of building frontier models is starting to choke off ...
DeepSeek unveils a groundbreaking AI training method, Manifold-Constrained Hyper-Connections, aimed at revolutionizing AI ...
ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. We develop constrained nuclear-electronic orbital density functional theory (CNEO–DFT) ...
Abstract: A distributed multiagent deep reinforcement learning algorithm (DMADRLA) with theoretical guarantees is proposed for the distributed nonconvex constraint optimization problem. This algorithm ...
Abstract: In this paper, the discrete time-varying equality constrained optimization (D-TV-ECO) problem based on discrete-time zeroing neural dynamic (DT-ZND) method is studied. Firstly, a continuous ...
The total processing time of the first workpiece in the first machine can be obtained directly from the data set, that is, the $f(W_{1},1)$ function can be called. In ...
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