The computational results on problems with up to 2750 variables strongly confirm our hypothesis that a combination of problem preprocessing, cutting planes, and clever branch-and-bound techniques ...

This repository demonstrates how to solve Linear Programming (LP) and Non-Linear Programming (NLP) problems using the Sequential Thinking Model Context Protocol (MCP). The approach breaks down complex ...

This repository contains a Python implementation of the Simplex algorithm for solving Linear Programming Problems (LPPs). The Simplex algorithm is an iterative method that optimizes a linear objective ...

Operations Research, Vol. 33, No. 4 (Jul. - Aug., 1985), pp. 803-819 (17 pages) We present methods that are useful in solving some large scale hierarchical planning models involving 0-1 variables.

Marshall, Paul W. "Linear Programming: A Technique for Analyzing Resource Allocation Problems." Harvard Business School Background Note 171-322, January 1971. (Revised November 1975 ...

Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-making problems but faces challenges in computational tractability and requires expert formulation. Current deep ...