Multi-platform coordinated mission planning under uncertainties

Military mission planning aims to coordinate a set of platforms with different capacities to accomplish a set of tasks under temporal, spatial and resource constraints. However, as military operations are intrinsically dynamic and uncertain, a solution (plan) corresponding to the deterministic circumstance is fragile due to unexpected events. To tackle this problem, this paper proposes a chance constrained programming model, which incorporates many uncertain factors, such as the durations, locations and resource requirements of tasks. The objective of mission planning is to coordinate the platforms to maximize the probability that all of tasks are completed successfully while satisfying the chance constraints. The problem is solved under a computational framework combining GA and Monte Carlo Simulation, the GA is used to solve the platform allocation and task scheduling while Monte Carlo Simulation is used to process the chance constraints. A mission instance is presented which demonstrates the usefulness of the proposed model and algorithm.