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The Turkish Armed Forces (TAF) assign more than 25,000 active duty personnel annually. TAF wants to obtain maximum utilization of its personnel by assigning the right person to the right job at the right time. To accomplish this task, decision-makers and personnel assignment staff should consider conflicting multiple objectives that create the widely known problem called .personnel assignment problem. To assist in this complicated task from a quantitative perspective, a preemptive goal programming approach was used to develop an integer programming (IP) model to capture the multiple objectives…mehr

Produktbeschreibung
The Turkish Armed Forces (TAF) assign more than 25,000 active duty personnel annually. TAF wants to obtain maximum utilization of its personnel by assigning the right person to the right job at the right time. To accomplish this task, decision-makers and personnel assignment staff should consider conflicting multiple objectives that create the widely known problem called .personnel assignment problem. To assist in this complicated task from a quantitative perspective, a preemptive goal programming approach was used to develop an integer programming (IP) model to capture the multiple objectives flexibly and interactively. A realistic size IP problem with random data was tested for computational efficiency and analysis. The mean solution time for different instances of the problem was reasonably small. An application of the methodology in an actual assignment decision support system of any large-scale government or non-government organization has a potential to help decision-makers make better use of their personnel.