In mathematical optimization, constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function...

single-objective optimization cases are presented. In the second part, test functions with their respective Pareto fronts for multi-objective optimization problems...

{\displaystyle g(x)=0~.} The solution corresponding to the original constrained optimization is always a saddle point of the Lagrangian function, which can...

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

PDE-constrained optimization is a subset of mathematical optimization where at least one of the constraints may be expressed as a partial differential...

class of algorithms for solving constrained optimization problems. A penalty method replaces a constrained optimization problem by a series of unconstrained...

separate box/linearly constrained version, BLEIC. R's optim general-purpose optimizer routine uses the L-BFGS-B method. SciPy's optimization module's minimize...

costs, and only estimates the value of the site as a whole. In constrained optimization in economics, the shadow price is the change, per infinitesimal...

for solving constrained optimization problems. They have similarities to penalty methods in that they replace a constrained optimization problem by a...

distinguished from, probabilistic optimization methods such as chance-constrained optimization. The origins of robust optimization date back to the establishment...