Cost-Effective Job Sequence Optimization for Minimizing Downtime in Flexographic Printing With Puma Optimizer Algorithm

This paper presents the Puma Optimizer (PO), a recent novel metaheuristic algorithm inspired by the hunting behaviors of pumas. The sequence of the color printing jobs in flexography industry play a significant role since downtime occurs every color changes. Therefore, this study focuses on optimizing printing job sequences to minimize cost, downtime, and maximize revenue. Three experiments of PO algorithm were conducted with varying population sizes and iteration sizes, all resulting in a total revenue of IDR265,434,000 (approximately ${\$}$17,426). Demonstrating the algorithm’s consistency despite different iteration paths. The exploration phase of the PO facilitates diverse solution generation through random searches, while the exploitation phase refines solutions by simulating puma hunting strategies, including ambush and sprinting.