Search alternatives:
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
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A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases
Published 2025Subjects: -
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The pseudocode for the NAFPSO algorithm.
Published 2025“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. …”
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PSO algorithm flowchart.
Published 2025“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. …”
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Scheduling time of five algorithms.
Published 2025“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. …”
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Convergence speed of five algorithms.
Published 2025“…A scheduling optimization model based on the particle swarm optimization (PSO) algorithm is proposed. …”
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Completion times for different algorithms.
Published 2025“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”
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The average cumulative reward of algorithms.
Published 2025“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”