DOI: https://doi.org/10.36347/sjpms.2025.v12i04.006

Pages: 130-139

This study applies permutation and combination techniques to optimize single machine job scheduling with precedence constraints and due dates. An R-based model was used to generate and evaluate all feasible job sequences, identifying the one that minimizes total completion time and penalty costs. Compared to traditional heuristics like SPT and EDD, the exhaustive combinatorial approach proved more effective in complex scheduling scenarios. The results highlight a data-driven method for improving scheduling efficiency, with practical relevance to manufacturing and project management.