@article{article_1598698, title={Capacity Balancing and Variation Minimization in Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times: A Mathematical Model and Matheuristic Approach}, journal={Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji}, volume={13}, pages={919–931}, year={2025}, DOI={10.29109/gujsc.1598698}, author={Ay, Merhad}, keywords={Parallel Machine Scheduling, Matheuristic, Optimization, Capacity Balancing}, abstract={In this study, a scheduling problem for unrelated parallel machines with sequence-dependent setup times, specifically in the context of tire production, is addressed. To solve this problem, a mathematical model and genetic algorithm-based matheuristic approaches have been developed. While the mathematical model provides accurate and effective solutions for small and medium scale problems, it exhibits limitations in time-constrained applications due to increased solution times for large-scale problems. In the study, two alternative matheuristic algorithms employing different crossover operators are proposed, and their ability to achieve near-optimal solutions for large-scale problems in short periods has been tested. Additionally, the classical random mutation operator was modified into a constrained random mutation operator tailored to the problem. Experimental results demonstrate that the proposed matheuristic algorithms significantly reduce solution times compared to the mathematical model, with the MA1 algorithm showing superior performance in terms of solution quality. This study offers substantial advantages in solving real-world problems by improving both solution time and quality. In the proposed matheuristic algorithm, the problem-specific chromosome structure, the initialization method for the initial population, and the constrained random mutation operator provide significant contributions to the literature for solving similar problems.}, number={3}, publisher={Gazi University}