We propose a parallel hybrid algorithm which aims to produce good solutions for large scale instances of the problem.
The configuration selection is supported by a heuristic search algorithm that ensures correctness and completeness while addressing time efficiency and scalability for large scale instances of the problem.
Historians have overlooked the intricacies of this first large-scale instance of absentee voting.
Detroit, more than a mere metaphor, is a striking and large-scale instance of something that has become pervasively wrong in America.
A very efficient and effective generalized Benders decomposition algorithm is then deployed, enabling the solution of large scale instances in reasonable time.
For solving large scale instances, the performance of the proposed ACO based meta-heuristic is improved by integrating it with a variable neighbourhood search.
In the last group of large scale instances derived from the gs group, the performance of MTZ is comparatively better.
First-order methods are the algorithms of choice for solving large-scale instances of the logistic regression problem.
Numerical results show that the proposed heuristic may obtain a nearly optimal value in a reasonable time for small and large-scale instances of the CSP.
We focus on mathematical programming approaches for the MCND and present three classes of methods that have been used to solve large-scale instances of the MCND: a cutting-plane method, a Benders decomposition algorithm, and Lagrangian relaxation approaches.
Afterwards, we validate the WD approach using simulated data by generating large-scale instances of our advanced electricity CRA problem.
