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Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear Programming: regression, classification and other engineering applications. Integer Linear Programming: Basics, ...

Linear programming, a method for optimizing a linear objective function subject to constraints, has seen significant advancements over the past century. From the Simplex algorithm in 1947 to the ...

Graph algorithms are integral for solving complex programming challenges. They provide methods for handling data relationships through graphs, which are essential in fields like network analysis, ...

Integer Linear Programming (ILP) is the foundation of combinatorial ... Large amounts of memory are usually needed for these algorithms, frequently in direct proportion to their execution times.

Algorithms for integer programming often take a first stab at a solution with linear programming, which is outwardly similar but allows the variables to vary continuously. Linear constraints, ...

We have provided the mathematical formulations and algorithms for solving two-stage and multistage stochastic mixed-integer linear/nonlinear programming problems. Endogenous uncertainty is ...

Abstract: By reformulating the linear multiplicative programming problem (LMP) as an equivalent nonconvex programming problem (EP), we present a new accelerating outcome space branch-and-bound ...