The determination of optimal time-in-grade for promotion at each rank in the Turkish Army

Ankara : The Department of Management and Institute of Economics and Social Sciences of Bilkent University, 2001.Thesis (Master's) -- Bilkent University, 2001.Includes bibliographical references leaves 93-95.The increasing pace of development in Human Resource Management makes an objective promotion system more valid than a system on subjective criteria in the Turkish Army. Therefore, the Army Headquarters tries to adapt an appropriate promotion system and criteria to The Turkish Army’s big hierarchical structure. Thus, the gap between the current and required officer inventory in the promotion system is thought to be minimized.In this study, the validity of a new promotion system, which is still under consideration in Human Resource Department of The Turkish Army, is evaluated against the current promotion system in The Turkish Army to establish a base for further quantitative research. The core of the study focuses on a non-linear optimization problem. The optimization is to obtain optimal values for time to wait at a rank until promotion. Optimal values of the selected promotion criteria, time – in-grade, are thought to make great contribution to further personnel decisions in The Turkish Army’s promotion system. The constructed model also supports the manpower planning requirements of the Army in determining the impact of existing policies on given promotion criteria over the long term.Şenerdem, Barbaros HayrettinM.S

Modeling the officer recruitment and manpower planning process in Turkish land forces

Cataloged from PDF version of article.The objective of this study is to improve the Turkish Land Forces officer accessions and manpower planning process. A model for planning officer accessions to Turkish Land Forces from sources that have different characteristics is presented. This model takes into account factors such as attritions, involuntary retirements, promotions and transitions to determine the impact of existing policies over the long term and to determine adjustments that might be required to reach authorized strength goals. The annual supply of accessions necessary to meet the strength goal with minimum deviations is determined. This manpower planning model is created using the modeling software GAMS.Pekmezci, ArzM.S

Optimizing active guard reserve enlisted manpower

The principal mission of the United States Army Reserve (USAR) is to maintain properly trained and equipped units available to promptly mobilize for war, national emergency, or other contingency operations, and to assist the Army in projecting land combat power. The Active Guard Reserve (AGR) program provides active duty reserve soldiers (officer and enlisted) to Army Reserve units and Regular Army units to support reserve missions. The proper placement and manning of the AGR force is critical to the readiness of the Army Reserve and to the strength of the Total Army. To assist the efforts of the Office of the Chief, Army Reserve, Program Analysis and Evaluation division (OCAR-PAE) to analyze the AGR enlisted force, this thesis develops an optimization model known as the AGR Enlisted Manpower Projection Model (AGR-EMPM). The primary purpose of the model is to serve as a manpower forecasting and decision analysis tool. The model aggregates at the career management field level by rank, active federal service, and time in grade. With a 7-year planning horizon, the model is ideally suited for near term policy analysis. To demonstrate the usefulness of the model, scenarios relating to stop loss and accessions are analyzed.http://archive.org/details/optimizingctiveg109455843Captain, United States Army ReserveApproved for public release; distribution is unlimited

Advanced Academic Degree Inventory Management (AADIM) Model

This research develops the Advanced Academic Degree (AAD) Inventory Model (AADIM) to employ an inventory management approach to select, educate, and assign officers to duties that require incumbents possessing advanced education in specialized technical disciplines. The AADIM offers an alternative approach to the US Air Force\u27s current billet-based Graduate Education Management System (GEMS). The entry model (AADIM-E) generates, via user inputs, a career field specific advanced education profile and then employs a Markov model to forecast the educational quotas necessary to achieve the desired profile within a prescribed period of time. The utilization model (AADIMU) uses an additive multi-attribute value function to ascribe a qualification score, based on a selected set of weighted criteria, to each officer with respect to each available duty assignment. An integer programming formulation is then solved to obtain an optimal matching between officers and assignments that maximizes the summed qualification scores. The research demonstrates that AADIM-E can be used to evaluate the feasibility and practicality of long-term policies such as career field manning, the desired proportion and timing of officers requiring advanced education, as well as the length of time allowed to achieve such goals. The AADIM-U yields an objective methodology to manage AAD officers, as long-term inventory assets, to yield substantially greater incumbency rates for AAD positions than historically achieved using the current GEMS process

The Application Of crashing A Project Network To Solve The Time/cost Tradeoff In Recapitalization Of The Uh-60a Helicopter

Since the beginning of project management, people have been asked to perform more with less in expeditious time while attempting to balance the inevitable challenge of the time/cost tradeoff. This is especially true within the Department of Defense today in prosecuting the Global War on Terrorism both in Afghanistan and Iraq. An unprecedented and consistent level of Operational Tempo has generated heavy demands on current equipment and has subsequently forced the need to recapitalize several legacy systems until suitable replacements can be implemented. This paper targets the UH-60A:A Recapitalization Program based at the Corpus Christi Army Depot in Corpus Christi, Texas. More specifically, we examine one of the nine existing project sub-networks within the UH-60A:A program, the structural/electrical upgrade phase. In crashing (i.e. adding manpower or labor hours) the network, we determine the minimal cost required to reduce the total completion time of the 68 activities within the network before a target completion time. A linear programming model is formulated and then solved for alternative scenarios. The first scenario is prescribed by the program manager and consists of simply hiring additional contractors to augment the existing personnel. The second and third scenarios consist of examining the effects of overtime, both in an aggressive situation (with limited longevity) and a more moderate situation (displaying greater sustainability over time). The initial linear programming model (Scenario 1) is crashed using estimates given from the program scheduler. The overtime models are crashed using reduced-time crash estimates. For Scenarios 2 and 3, the crashable times themselves are reduced by 50% and 75%, respectively. Initial results indicate that a completion time of 79.5 days is possible without crashing any activities in the network. The five-year historical average completion time is 156 days for this network. We continue to crash the network in each of the three scenarios and determine that the absolute shortest feasible completion times, 73 days for Scenario 1, 76 days for Scenario 2, and 77.5 days for Scenario 3. We further examine the models to observe similarities and differences in which activities get targeted for crashing and how that reduction affects the critical path of the network. These results suggests an in-depth study of using linear programming and applying it to project networks to grant project managers more critical insight that may help them better achieve their respective objectives. This work may also be useful as the groundwork for further refinement and application for maintenance managers conducting day-to-day unit level maintenance operations