Large Scale Optimisation
It is very difficult for existing algorithms to solve large problems with many variables. One popular approach to alleviating these problems is to divide the large problems into a number of subproblems, and to then solve these subproblems using independent computer processors. This can be suboptimal because when one subproblem is optimised, it may cause one or more other subproblems to become deoptimised. This occurs because the variables in one subproblem interact with those of another. In this research, we (Hasan, Daryl and Sarker) have identified such dependencies and have tailored the subproblems to limit such dependencies. Results so far, have supported the merits of this approach.