Learning-based hybrid method improves circular e-waste network optimization
A learning-based hybrid optimization method reduced median normalized IGD+ by 60.6% versus standard NSGA-II in a modeled circular e-waste supply ...
A learning-based hybrid optimization method reduced median normalized IGD+ by 60.6% versus standard NSGA-II in a modeled circular e-waste supply ...
The open-source FHOPS platform combines exact and heuristic optimization, disturbance testing and traceable evidence generation for forest harvest scheduling in ...
A Yangtze River network model found that two fixed methanol hubs using cross-port bunker barges could cut total system costs ...
Turning a plain-English description of a logistics headache into a working mathematical model has long been a task reserved for ...
Researchers have developed a network optimization model that places fuel breaks to minimize wildfire spread while safeguarding woodland caribou migration ...
Researchers at KAIST have developed a two-stage optimization framework that embeds launcher-dependent deployment constraints directly into satellite constellation pattern design, ...
Researchers at Shanghai Maritime University have developed an improved evolutionary algorithm that simultaneously schedules yard cranes and vehicle parking positions ...
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© 2025 Scienmag - Science Magazine