Optimizing plastic product manufacturing scheduling: an integrated approach to minimize setup costs and tardiness with preventive maintenance considerations

Abstract

In the competitive landscape of plastic product manufacturing, optimizing production scheduling is crucial for enhancing efficiency and reducing costs. This paper presents an integrated approach to address the unrelated parallel machine scheduling problem (UPMSP) with a focus on minimizing setup costs and tardiness penalties, while also considering the necessity of preventive maintenance. We incorporate practical constraints such as release time, machine eligibility, and delivery due dates into our model to ensure its applicability to real-world manufacturing scenarios. We propose a mixed-integer linear programming model designed to minimize the total costs associated with setup and tardiness. To solve this complex problem, we develop a constructive heuristic and an adaptive large neighborhood search (ALNS) algorithm, which introduces novel destroy and repair operators. These algorithms are tailored to the specific structure of the UPMSP and are tested through a case study involving a real plastic product manufacturer. Results from the case study demonstrate that our proposed solution method significantly outperforms the company's current planning approach, achieving a reduction in total costs by 73.11%. Furthermore, the ALNS algorithm's performance is validated through numerical experiments on a range of randomly generated instances, showcasing its ability to provide high-quality solutions within practical computation times.