Solving the faculty staffing problem by goal programming  

Oleh:

Mabini, Marilyn C.

Jenis: Article from Proceeding
Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-12.
Topik: faculty staffing; mixed-integer nonlinear goal programming; deviational variables
Fulltext: 2012.pdf (322.66KB)

Isi artikel

We present a mixed-integer nonlinear goal programming model for the faculty staffing problem covering selected departments of an academic institution. We use the following goals: (1) student credit units, (2) faculty to student ratio, (3) proportion of faculty members teachingfull-time, (4) proportion of faculty members with graduate degrees, and (5) faculty research units. The model includes a faculty salary budget constraint. We solve two versions of the model. In one version, the goals are treated with equal priorities; while in the second version, the goal constraints for goals (3) and (4) are changed to “>=” constraints. The models are solved using LINGO, an optimization modeling software from Lindo Systems, Inc.While version 1 is solved as one problem, the second version is solvedas a series of sub-problems, each one striving to meet a goal as closely as possible. Here, the solution obtained for each sub-problem is incorporated in the next one. When all the goals have been addressed, the salary budget constraint is removed and the model is solved with the objective of minimizing the total cost of faculty salaries. Owing to the nonlinear nature of the formulations, at best only local optima were found. Results indicate how the institution can meet government-specified goals and improve its cost performance at the same time. The model promises to be a useful decision support tool for academic administrators in their task of meeting higher education quality requirements, while satisfying institution-based concerns.

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