Anthropic research reveals AI models perform worse with extended reasoning time, challenging industry assumptions about test-time compute scaling in enterprise deployments.

This study proposes a comprehensive strategy to optimize the operation of real-world gas pipeline networks and support decision-making. The goal is to improve environmental sustainability by ...

ABSTRACT: This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to ...

When tackling linear programming (LP) models under time constraints, you're essentially trying to find the best outcome within a defined set of rules and limited resources. LP, a mathematical ...

Learn how to tackle resource constraints in linear programming for optimal operations research outcomes.

This letter proposes a multi-agent distributed solution for linear programming (LP) problems with time-invariant box constraints on the decision variables and possibly time-varying inequality ...

To obtain a minimum backbone grid, a mixed integer linear programming (MILP) model with network connectivity constraints for a minimum backbone grid is proposed. In the model, some constraints are ...

In this paper we develop a generic mixed bi-parametric barrier-penalty method based upon barrier and penalty generic algorithms for constrained nonlinear programming problems. When the feasible set is ...

The DK–L distance was used as the inter-class distance, and the mixed-integer linear programming is used to maximize the minimum inter-class distance with additional constraints.

Many problems of interest for cyber-physical network systems can be formulated as mixed-integer linear programs in which the constraints are distributed among the agents. In this paper, we propose a ...