We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...

Research and investment in artificial intelligence (AI) have rapidly expanded over the past decade. The International Data Corporation predicts that global spending on cognitive and AI systems will ...

The Journal of the Operational Research Society, Vol. 55, No. 7, Part Special Issue: Local Search (Jul., 2004), pp. 705-716 (12 pages) The Bin Packing Problem and the Cutting Stock Problem are two ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

This is where Process Optimization with Simulation emerges as a critical tool, offering a powerful way to model, analyze, and ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Co., Ltd. recently announced that its patent for "An Artificial Intelligence Optimization Method for Natural Gas Liquefaction Systems" has been authorized by the National Intellectual Property ...