Capacity Analysis for Aircrew Training Schools - Estimating Optimal Manpower Flows Under Time Varying Policy and Resource Constraints

Interactions of the AnyLogic agent, Java classes and the IBM CPLEX ILP Solver.jpgCapacity analysis for systems with time varying constraints remains a challenge in Operations Research. This is particularly relevant when dealing with Defence manpower supply which is subject to frequent temporal policy and resource changes. Past solutions of the problem typically resort to simulating training flows, and in recent years simulation combined with optimisation solutions have become popular. This paper is motivated by the need to optimally provide aircrew supply in one of the Australian Navy’s training schools.

The Royal Australian Navy (RAN) has recently acquired a fleet of new aircraft. In order to achieve and maintain an adequate workforce level, the relevant training flows for the new aircrew has to be established within a given lead time. The training pipeline for the aircrew (pilots, observers and aircrewmen) finishes with conversion training, where students specialise in flying a particular aircraft type. Defence Science and Technology (DST) Group within the Australian Department of Defence was asked to determine the number of aircrew that could graduates in a conversion school, by scheduling the available resources: aircraft, simulators and instructors. To this end we have developed a simulation-optimisation approach for analysing the capacity of this training unit. It uses a Discrete Event Simulation (DES) approach to model the day-to-day operations of the training school, representing the training schedules, allocate aircraft, simulators and supplementary workforce resources. The DES also models constraints pertaining to resource availability including instructors’ available hours, the training schools’s operating hours and other business rules. An integer linear programming optimisation (ILP) algorithm is invoked by the simulation at every time slot to create step-wise optimal schedule to assign students, resources and instructors to classes.


Interactions of the AnyLogic agent, Java classes and the IBM CPLEX ILP Solver

Interactions of the AnyLogic agent, Java classes and the IBM CPLEX ILP Solver

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