Tabu Search-Based Tool for Faculty Allocation

This work proposes a tool based on the Tabu Search metaheuristic to optimize faculty allocation at SME of ICMC-USP. The solution was developed with a modular architecture, composed of independent blocks for neighborhood generation, evaluation, tabu list verification, and incumbent solution updating, facilitating maintenance and extensibility. Tests conducted with real data from two semesters allowed for the calibration of penalties applied to violations of soft constraints and the adjustment of operational parameters, such as the tabu list size and the maximum number of iterations. The results demonstrated significant improvements in the distribution of teaching workload and greater adherence to institutional constraints. The tool integrates automated optimization processes with a manual validation stage, ensuring flexibility and efficiency in the allocation process, with the potential to support decision-making in complex academic contexts.