STATISTICAL SENSITIVITY ANALYSIS OF THE REPLENISHMENT AT SEA PLANNER

Abstract

Underway replenishment is required for ships to operate at sea without port calls. The Replenishment At-Sea Planner (RASP) provides optimized schedules while considering a myriad of factors. We develop a statistical sensitivity analysis of the effect changes to RASP inputs have on outputs such as Combat Logistics Force (CLF) fuel consumption, CLF ship underway percentage, and combatant supply safety stock level. The resulting statistical models are useful for logistical planners if RASP is unavailable, yet decisions regarding the schedule must be made and avoid needing to re-solve RASP. Models of western Pacific scenarios schedule the replenishment of Carrier Strike Groups (CSGs) (e.g., one Aircraft Carrier, one Cruiser, and two Destroyers) and CLF ships. In a one-CSG scenario, we develop a statistical model that predicts CLF fuel consumption and percent of time CLF ships are underway with an average error of 4.6% and 13.7% respectively and these predictions are consistently below the actual values. In a two-CSG scenario, a statistical model either over- or underpredicts CLF fuel consumption based on regional boundary constraints on CLF operations. Predictions are consistently between -26% and -14% under and 19% and 27% over. In order of importance, the number of days in the CSG sustainment cycle, regional boundary limitations imposed on CLF ships, and the number of CLF ships available are the most influential to RASP outputs.