Ozel, OykuYilmaz, Gorkem2025-11-032025-11-0320252405-8963https://doi.org/10.1016/j.ifacol.2025.09.285This study introduces a production planning model designed to address the complexities of shift and overtime scheduling while minimizing frequent changes in production settings over short intervals. By incorporating flexible shift and overtime scheduling, the model enables companies to efficiently manage production, inventory, and backlogs while remaining responsive to fluctuating customer demands. The proposed mixed-integer linear programming model (MILP) optimizes production, inventory, and backorder costs through product-production line allocation, shift, and overtime decisions. The objective function minimizes total costs, including fixed and variable production costs, inventory holding costs, backorder costs, shift and overtime transition costs, and idle capacity penalties. Computational experiments validate the effectiveness of the model, demonstrating its ability to improve production efficiency, reduce operational costs, and adapt to dynamic demand conditions. The findings highlight the potential of the proposed approach to support efficient and flexible production planning in dynamic manufacturing environments. Copyright (C) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)eninfo:eu-repo/semantics/openAccessCapacity PlanningProduction PlanningMixed Integer Linear Programming (MILP)Shift and Overtime SchedulingBackloggingConference Object10.1016/j.ifacol.2025.09.2852-s2.0-105018803566