New dual-polarity Ising/QUBO framework encodes SAT so that ground states correspond to short implicants, with parameter regimes for minimality and empirical results leaving about one-third of variables unassigned on random 3-SAT.
Tabu search, Part II,
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CHAP's cross-platform portfolio finds feasible solutions for 47 of 50 MIP benchmark instances in five minutes, beating Gurobi (44) and cuOpt (43) by coordinating GPU tabu search with CPU fix-and-propagate and feasibility pump via a shared pool.
Introduces a beam-search heuristic for random subset sum that uses meshing to obtain inverse-quadratic expected error decay in linearithmic time.
A quantum-assisted agentic DAI framework formulates microgrid dispatch as QUBO problems solved by solver portfolios with agentic selection and belief-shaped storage valuation, achieving exact optimum in a 24-hour simulation with 97.83% renewable utilization.
A digital twin framework integrates agent-based decision support and metaheuristic optimization to dynamically model and optimize EV charging infrastructure, policies, and renewables in a Hanoi university campus setting.
citing papers explorer
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Computing Short SAT Implicants via Ising/QUBO Encodings
New dual-polarity Ising/QUBO framework encodes SAT so that ground states correspond to short implicants, with parameter regimes for minimality and empirical results leaving about one-third of variables unassigned on random 3-SAT.
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CHAP: A Hybrid GPU-CPU Heuristic for MIP
CHAP's cross-platform portfolio finds feasible solutions for 47 of 50 MIP benchmark instances in five minutes, beating Gurobi (44) and cuOpt (43) by coordinating GPU tabu search with CPU fix-and-propagate and feasibility pump via a shared pool.
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Inverse Quadratic Decay in Random Subset Sum
Introduces a beam-search heuristic for random subset sum that uses meshing to obtain inverse-quadratic expected error decay in linearithmic time.
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A Quantum-Assisted Agentic Distributed Artificial Intelligence Framework for Deadline-Bounded Orchestration of Hybrid Renewable Microgrids
A quantum-assisted agentic DAI framework formulates microgrid dispatch as QUBO problems solved by solver portfolios with agentic selection and belief-shaped storage valuation, achieving exact optimum in a 24-hour simulation with 97.83% renewable utilization.
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A Digital Twin Framework for Decision-Support and Optimization of EV Charging Infrastructure in Localized Urban Systems
A digital twin framework integrates agent-based decision support and metaheuristic optimization to dynamically model and optimize EV charging infrastructure, policies, and renewables in a Hanoi university campus setting.