Linear programming models can help create efficient and fair staff schedules that balance these factors and comply with regulations and policies. For example, a linear programming model can assign ...

AI models can be complex, opaque, and hard to interpret, particularly when they involve nonlinear functions, high-dimensional features, or multiple objectives. This can create issues related to ...

Data for a linear programming problem resembles the data for side constraints and nonarc variables supplied to PROC NETFLOW when solving a constrained network problem. It is also very similar to the ...

Abstract: For the purpose of improving the capacity utilization rate of rail transit lines, combined with the expansion network of rail transit space-time passenger flow, a linear programming model ...

Variables, constraints, and linear expressions are available as Java objects to make model building as easy as possible. Decision variables as well as their bounds and objective coefficients can be ...

apply license of the package mosek on https://www.mosek.com/products/academic-licenses/ and move the license file 'mosek.lic' to folder /home/username/mosek/mosek.lic ...

Abstract: In this article, the problem of constructing the single-track gray code (STGC) encoders is considered. STGCs are very useful in absolute position encoding for angular sensors which are used ...

Diet models based on goal ... Briend A . Linear and nonlinear programming to optimize the nutrient density of a population's diet: an example based on diets of preschool children in rural Malawi.

Mixed Integer Linear Programming (MILP) is essential for modeling ... To address this shortcoming, we take a foundation model training approach, where we train a single deep learning model on a ...