Planning for promotions is far harder than planning for routine demand and replenishment. The solution lies in a hybrid ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

OpenAI inference cost reduction cut ChatGPT guest traffic from tens of thousands of Nvidia GPUs to just a couple hundred, ...

In 2022, global production of construction materials accounted for more than 7% of total carbon emissions. But how many of ...

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

Abstract: This letter addresses the distributed constrained optimization problem over multi-agent networks, where a group of agents collaboratively minimizes the average of their locally held ...

LOS ANGELES — Victor Wembanyama is doing something wrong. The 7-foot-4 unicorn, still in the early stages of rewriting how basketball is played, just made a move few in the world can. But it’s the ...

Traditional approaches to analytical method optimization (e.g., univariate and “guess-and-check”) can be time-consuming, costly, and often fail to identify true optima within the parameter space.

ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...

ABSTRACT: In this paper, we investigate the convergence of the generalized Bregman alternating direction method of multipliers (ADMM) for solving nonconvex separable problems with linear constraints.