A next-gen Lagrange-Newton solver for nonconvex constrained optimization. Unifies barrier and SQP methods in a generic way, and implements various globalization flavors (line search/trust region and ...

Task description should provide enough information for other members to understand what was updated or changed, e.g., fixing bugs, adding features, refactoring code. After that, use the git push ...

Linear semi-infinite programming (LSIP) is a branch of optimisation that focuses on problems where a finite number of decision variables is subject to infinitely many linear constraints. This ...

In this study, we consider the problem of scheduling a set of jobs with sequence-dependent setup times on a set of parallel production cells. The objective of this study is to minimize the total ...

Abstract: In many real-life situations, it is necessary to optimize two or more objects simultaneously. In such problems, the objectives under consideration conflict with each other, and optimizing a ...

Computer programs to solve linear programming problems by the simplex method have existed since the early 1950s. They remain the central feature of today's mathematical programming systems. There has ...

In this paper we study the problem of locating multiple facilities in convex sets with fuzzy parameters. This problem asks to find the location of new facilities in the given convex sets such that the ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...