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dc.contributor.authorDeWolfe, Dean
dc.contributor.authorStevens, James
dc.contributor.authorWood, R. Kevin
dc.date.accessioned2014-01-22T19:08:23Z
dc.date.available2014-01-22T19:08:23Z
dc.date.issued1993
dc.identifier.urihttp://hdl.handle.net/10945/38425
dc.descriptionNaval Research Logistics, 40, pp. 143-160.en_US
dc.description.abstractThe United States military frequently has difficulty retaining enlisted personnel beyond their initial enlistment. A bonus program within each service, called a Selective Reenlistment Bonus (SRB) program, seeds to enhance reenlistments and thus reduce personnel shortages in critical military occupational specialties (MOSs). The amount of bonus is set by assigning “SRB multipliers” to each MOS. We develop a nonlinear integer program to select multipliers which minimize a function of deviations from desired reenlistment targets. A Lagrangian relaxation of a linearized version of the integer program is used to obtain lower bounds and feasible solutions. The best feasible solution, discovered in a coordinate search of the Lagrangian function, is heuristically improved by apportioning unexpended funds. For large problems, a heuristic variable reduction is employed to speed model solution. U.S. Army data and requirements for FY87 yield a 0-1 integer program with 12,992 binary variables and 273 constraints, which is solved within 0.00002% of optimality on an IBM 3033AP in less than 1.7 seconds. More general models with up to 463,000 binary variables are solved, on average, to within 0.009% of optimality in less than 1.8 minutes. The U.S. Marine Corps has used a simpler version of this model since 1986.en_US
dc.rightsdefined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleSetting Military Reenlistment Bonusesen_US
dc.typeArticleen_US
dc.contributor.departmentOperations Research (OR)
dc.subject.authorReenlistment bonus, nonlinear integer program, Lagrangian relaxationen_US


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