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 ...
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 ...
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 ...
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 ...
In modern computing, solving complex optimization problems has always been a significant challenge. Recently, a research team from Canada developed a new type of photonic Ising machine capable of ...
In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...
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