Bilevel optimisation represents a class of hierarchical decision-making processes where two interrelated optimisation problems are solved sequentially. In such problems, the upper-level (or leader) ...

Fuzzy optimisation has emerged as a vital framework for addressing decision-making and extremum problems where data ambiguity and uncertainty preclude the direct application of classical optimisation ...

Over the past decades, researchers and companies worldwide have been trying to develop increasingly advanced quantum computers. The key objective of their efforts is to create systems that will ...

Scientists have demonstrated a breakthrough application of neutral-atom quantum processors to solve problems of practical use. A collaboration between Harvard University with scientists at QuEra ...

There are, generally speaking, two types of people in the mathematical optimization software field: • Optimization solver developers: The technical experts who devise and implement the algorithms that ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

Cambridge, UK, July 22, 2021 – In a development the company said “is likely to set a new industry standard,” scientists at Cambridge Quantum (CQ) have developed a new algorithm for solving ...

HSBC has begun collaborating with Terra Quantum to investigate using hybrid quantum applications to tackle optimisation challenges. One example of such an issue is collateral optimisation, which is ...

A group of researchers at the Massachusetts Institute of Technology have devised a potentially more effective way of helping computers solve some of the toughest optimization problems they face. Their ...

Over the course of my 25-year career in the mathematical optimization software industry, I’ve lost count of how many times I’ve been asked this question: “Can you tell me what mathematical ...

In this paper, we first recall the three restrictive hypotheses outside which it is not possible to speak of an optimum, and then we specify in which context (decision aid) this article is located.

We were visiting a hedge fund some years back when we had our first taste of the problem with mean-variance optimization—the tool advisors use to balance risk and reward in client portfolios. We ...