Near-optimal scheduling and allocation for DoD missions is complicated by many factors, including multiple measures of effectiveness, mixed-initiatives, heterogeneity of systems and non-uniformity of homogenous systems; these factors contribute to a complex planning problem with non-linear, combinatorial, and continuous components that is further complicated by information uncertainty. In Navy, mine counter measure missions, planning entails components of the vehicle routing problem with time windows and flexible flowshop scheduling with pre-emptive maintenance. We present a multiobjective mine counter measures problem formulation and describe the non-dominated scheduler, a scheduling programme that parametrically explores continuous dimensions of the decision space, stochastically samples from exponentially large decision spaces, and uses surrogate metrics to bound computational complexity. This provides mission commander with a non-dominated set of alternative plans. This scheduler has been integrated into existing tools and is being evaluated by the US Navy for extension and integration into next-generation mine warfare decision aids.
All Science Journal Classification (ASJC) codes
- Management Science and Operations Research