A multi-cloud MLOps framework improves AI service reliability through automated deployment, canary releases, and ...

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 ...

In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

Abstract: Dynamic constrained multi-objective optimization problems (DCMOPs) present significant challenges due to the evolving nature of both objectives and constraints. These problems require ...

Stanford's BurgerAI beat the Big Mac in a blind taste test with 101 diners, proving AI can invent recipes humans actually ...

Bringing multiple problems to a single general practitioner (GP) appointment raises various ethical issues, all of which emerge from the central tension between the total number of problems brought to ...

Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which optimization actually moved the needle.

Abstract: Multi-objective multi-point shortest path planning problems are commonly encountered in real-world applications. Numerous path planning algorithms have been proposed to accommodate different ...