Combinatorial optimisation algorithms are central to addressing problems in which the goal is to select an optimal solution from a finite set of alternatives. These algorithms have evolved ...

Cambridge Quantum reveals new algorithm for solving combinatorial optimization problems with business use-cases.

Most of the recent work on 2-stage stochastic combinatorial optimization problems has focused on minimization of the expected cost or the worst-case cost of the solution. Those two objectives can be ...

One must make sure that the optimization algorithms used can reach a good-enough solution in a reasonable time for a realistically large number of ports and vehicles.

Rigetti was selected by the Defense Advanced Research Projects Agency (DARPA) to advance the state-of-the-art in quantum algorithms for solving combinatorial optimization problems as part of the ...

The traveling salesman problem is considered a prime example of a combinatorial optimization problem. Now a Berlin team led by theoretical physicist Prof. Dr. Jens Eisert of Freie Universität ...

Randomized algorithms for combinatorial and discrete optimization Randomized algorithms for machine learning on networks Deadlines CU Internal Deadline: 11:59pm MST May 2, 2022 DOE Pre-Application ...

Quantum annealing (QA) is a cutting-edge algorithm that leverages the unique properties of quantum computing to tackle complex combinatorial optimization problems (a class of mathematical problems ...

Lysa Porth, Jeffrey Pai, Milton Boyd, A Portfolio Optimization Approach Using Combinatorics With a Genetic Algorithm for Developing a Reinsurance Model, The Journal of Risk and Insurance, Vol. 82, No.