generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from...

convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard. A convex optimization problem...

Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the...

In mathematical optimization theory, duality or the duality principle is the principle that optimization problems may be viewed from either of two perspectives...

Continuous optimization is a branch of optimization in applied mathematics. As opposed to discrete optimization, the variables used in the objective function...

(often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem. Gurobi is included in the...

Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute...

hyperparameter optimization methods. Bayesian optimization is a global optimization method for noisy black-box functions. Applied to hyperparameter optimization, Bayesian...

Bilevel optimization is a special kind of optimization where one problem is embedded (nested) within another. The outer optimization task is commonly referred...

researchers active in optimization. The MOS encourages the research, development, and use of optimization—including mathematical theory, software implementation...