Welcome to the InfoSci Platform
A Network Approach to Identifying Military Fleet Replacement Strategies

A Network Approach to Identifying Military Fleet Replacement Strategies

Patrick J. Driscoll, Harry Newton, Russell Mosier
Copyright: © 2013 |Volume: 4 |Issue: 4 |Pages: 18
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781466635791|DOI: 10.4018/ijoris.2013100103
Cite Article Cite Article

MLA

Driscoll, Patrick J., et al. "A Network Approach to Identifying Military Fleet Replacement Strategies." IJORIS vol.4, no.4 2013: pp.39-56. http://doi.org/10.4018/ijoris.2013100103

APA

Driscoll, P. J., Newton, H., & Mosier, R. (2013). A Network Approach to Identifying Military Fleet Replacement Strategies. International Journal of Operations Research and Information Systems (IJORIS), 4(4), 39-56. http://doi.org/10.4018/ijoris.2013100103

Chicago

Driscoll, Patrick J., Harry Newton, and Russell Mosier. "A Network Approach to Identifying Military Fleet Replacement Strategies," International Journal of Operations Research and Information Systems (IJORIS) 4, no.4: 39-56. http://doi.org/10.4018/ijoris.2013100103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The Motor Transport Program Office for the U.S. Marine Corps (PM MT) manages the Light Tactical Wheeled Vehicle (TWV) fleet and must make decisions each year about vehicle procurements, overhauls, and retirements. These decisions are based on projected costs to maintain current vehicles, estimates of the remaining useful life of the vehicles, availability of new vehicles and individual vehicle capabilities and budgets. In this portfolio analysis, the authors developed a flexible, optimization-based methodology for supporting these fleet level decisions based on cost estimates, initial inventories, operational tempo (OPTEMPO), and approved requirements documents (capabilities). Accommodating user requirements, the model uses Frontline Solver in an Excel environment, leveraging network flow constraints to decrease runtime to solution so that multiple runs of scenario excursions can expose advantages and disadvantages of different fleet management policies. A user interface was developed to allow for batch runs using design of experiment or parametric analysis of the data. The interface also helped manage the model complexity of roughly 6,000 decision variables that were developed dynamically depending on the input assumptions.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.