A novel algorithm for mixed integer nonlinear optimization problems

The main objective of this research is to develop a computationally efficient hybrid algorithm for the constrained mixed integer, nonlinear optimization problems (MINLPs). The developed algorithm provides a general framework for solving a large class of problems formulated as MINLPs. Although the utility of the algorithms is tested on sample graph-partitioning problems, the application is not limited to any particular field of application. For instance the coordinated decision and control problem for multiple unmanned aerial vehicles (UAVs) can be cast as a MlNLP and hence efficiently solved by the proposed technique.