Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Against the backdrop of global change—characterized by climate warming, shifting precipitation patterns, and intensified anthropogenic disturbances—the ...
Aerospace and Mechanical Insider on MSN
Multi-agent reinforcement learning driving smart factory agility
At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...
Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which optimization actually moved the needle.
Abstract: Through the use of solar and wind energy systems, this study offers a novel approach to the Short-Term Hydrothermal Generation Scheduling (STHTGS) problem. Reducing thermal units total fuel ...
Abstract: Constrained multi-objective problems (CMOPs) are tricky, because it is difficult to handle multiple objectives and constraints simultaneously. Most existing algorithms perform well on CMOPs ...
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