Constant Constraint Matrix Approximation: A Robust, Parallelizable Constraint Method for Molecular Simulations

A New Method for Solving Constraint Satisfaction Problems

Many important problems in Artificial Intelligence can be defined as Constraint Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constraints on the values of those variables (these problems are also called Consistent Labeling Problems (CLP), in which “Labeling" means assigning a value to a variable.) Sol...

A New Method for Solving Constraint Satisfaction Problems

Many important problems in Artificial Intelligence can be defined as Constraint Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constraints on the values of those variables (these problems are also called Consistent Labeling Problems (CLP), in which “Labeling means assigning a value to a variable.) Solu...

A Mathematical Method for Managing the System Constraint

The goal of theory of constraints (TOC) is to maximize output, which is achieved byidentifying and managing the critically constrained resources. To manage the constraints, Goldrattproposed five focusing steps (5FS). If we increase constrained output, the output of system will beincreased. In this paper, we focus on step four of the 5FS and use the remained capacity of nonconstraintto elevate t...

Differential Equation of Sensitivity Matrix for Final Velocity Constraint

LINCS: A linear constraint solver for molecular simulations

In this article we present a new LINear Constraint Solver (LINCS) for molecular simulations with bond constraints. The algorithm is inherently stable, as the constraints themselves are reset instead of derivatives of the constraints, thereby eliminating drift. Although the derivation of the algorithm is presented in terms of matrices, no matrix matrix multiplications are needed and only the non...