Optimized Green Unrelated Parallel Machine Scheduling Problem Subject to Preventive Maintenance

• Published in: Designs Vol. 9; no. 2; p. 26
• Main Author: Almasarwah, Najat
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2025
• Subjects: Algorithms; Customer satisfaction; Datasets; Energy consumption; Energy efficiency; Genetic algorithms; green scheduling; Heuristic; Heuristic methods; Integer programming; Linear programming; Maintenance; Mathematical models; Mathematical optimization; Mathematical research; Methods; Optimization; Optimization algorithms; Performance evaluation; Preventive maintenance; products returned early; Scheduling; Scheduling (Management); unrelated parallel machine; Working conditions; Jordan
• ISSN: 2411-9660; 2411-9660
• DOI: 10.3390/designs9020026

Manufacturing areas typically conduct machine maintenance to prevent early failures and to ensure a safe working environment and efficient production. In this study, the green unrelated parallel machine scheduling problem (GUPMSP) is studied. Besides preventive maintenance, machine availability and non-preemption are considered. A globally optimal solution (mathematical model) and local optimal solution (a modified Moore heuristic algorithm) are used to optimize the number of products returned early in the GUPMSP. Three datasets, namely, a most favorable case, an average case, and a least favorable case, are created to test the performance of the two solutions’ approaches. The results demonstrate the ability of the mathematical model to dominate the results of the modified Moore’s algorithm in the tested datasets. However, optimizing the number of products returned early in the UPMSP with preventive maintenance reduces costs as a step to support the concept of sustainability and enhance efficiency.