Modeling Nonlinear Optimization Problems in CPLEX: Methods and Best Practices
IBM’s CPLEX, predominantly recognized for its prowess in linear and quadratic programming, also offers capabilities to tackle certain types of nonlinear optimization problems. This article delves into the strategies for modeling and solving nonlinear problems using CPLEX, accompanied by best practices and illustrative examples from hypothetical real-world scenarios.
The Future of Optimization: AI, Machine Learning, and Gurobi’s Role
In an era where artificial intelligence (AI) and machine learning (ML) are reshaping industries, the field of mathematical optimization isn’t left behind. Gurobi, a leading optimization solver, is at the forefront of this transformation. This article explores how Gurobi intersects with AI and ML, its potential integrations, and the evolving landscape of optimization problems in the context of these advancements.