Accession Number : ADA285512


Title :   A Cost Simulation Tool for Estimating the Cost of Operating Government Owned and Operated Ships


Descriptive Note : Masters Thesis


Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA


Personal Author(s) : Redman, Terry L


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a285512.pdf


Report Date : Sep 1994


Pagination or Media Count : 149


Abstract : The cost of operating ships is difficult to predict. A historic ship's operating cost database is maintained by the Military Sealift Command (MSC); but, it is very difficult to extract or manipulate the data to support prediction or regression analysis. An alternative was sought that would reduce the effort for the user when attempting to make predictions from the data. If the data for each cost category (salary, training, fuel, port and miscellaneous, subsistence, ship's equipage, and voyage repairs) could be well approximated using probability distributions, then the costs of an operational scenario, with estimates of the uncertainties, could be obtained through use of a Monte Carlo simulation. The MSC data was divided into subsets, one for model fitting and one for validation. Once probability distributions had been fit to the data, a Monte Carlo simulation tool was developed using the Crystal Ball simulation add in to Microsoft Excel. The data analysis and cost model were then validated using empirical data. Based on the results, the Cost Simulation model provides a useful tool for predicting operating costs and supports sensitivity analysis of various ship's operating cost scenarios. Monte Carlo simulation, Data analysis.


Descriptors :   *MATHEMATICAL MODELS , *NAVAL VESSELS , *COST MODELS , DATA BASES , COMPUTERIZED SIMULATION , VALIDATION , PROBABILITY DISTRIBUTION FUNCTIONS , THESES , MATHEMATICAL PROGRAMMING , FUELS , SALARIES , REPAIR , REGRESSION ANALYSIS , MONTE CARLO METHOD , COST ESTIMATES , TRAINING , PREDICTIONS , SCENARIOS , UNCERTAINTY


Subject Categories : Economics and Cost Analysis
      Operations Research
      Marine Engineering


Distribution Statement : APPROVED FOR PUBLIC RELEASE