This paper describes an optimisation system developed specifically for dynamic real-time schedules. Here we combine advances in self-organising fuzzy logic and optimisation to create a controller to manage the computational time available to the fleet, in order to insure the fast insertion of appropriate new jobs. The controller prioritises jobs entering the system and decides based on past experience, which vehicle is most capable to optimally fulfill the constraints of each new job. Following the insertion of the new jobs, optimisation is performed on the selected vehicle's schedule thereby striving for the best answer under the realtime environment. The controller is developed to select the most suitable additions to the schedule, creating an initial cost for the inclusion of these jobs, in the least amount of time.