Parallel machine scheduling with common due windows

• Published in: The Journal of the Operational Research Society 2010-04, Vol.61 (4), p.640-646
• Main Authors: Huang, R-H, Yang, C-L, Huang, H-T
• Format: Article
• Language: English
• Subjects: Algorithms; Applied sciences; Business and Management; Data processing; Data types; due windows; Exact sciences and technology; Fines & penalties; Firm modelling; Genetic algorithms; Integer programming; Inventory control, production control. Distribution; Job shops; Lateness; Machinery; Management; on-time; operation scheduling; Operational research and scientific management; Operational research. Management science; Operations research; Operations Research/Decision Theory; parallel machine; Production scheduling; Schedules; Scheduling; Scheduling, sequencing; Studies; Test data; Theoretical Paper; Theoretical Papers; Time dependence
• ISSN: 0160-5682; 1476-9360
• DOI: 10.1057/jors.2008.184

With the prevalence of on-time scheduling, timely product submission has become a crucial contributor to customer satisfaction. Studies examining on-time scheduling primarily seek to determine the minimum weighted sum of earliness and tardiness penalties. This study assumes that all machines are identical. Furthermore, this study assumes that jobs are independent and share a common due date window when investigating scheduling problems involving parallel machines with a minimum total number of early and tardy jobs (or maximum number of on-time jobs). This study presents related theorems and a novel simplified algorithm based on the problem. Additionally, rule characteristics are examined, and simulated data are used to verify the effectiveness and timeliness of the proposed algorithm. The theoretical proof and data test results all indicate that the proposed approach obtains the best solution within the shortest time.