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Journal of Scheduling

, Volume 15, Issue 4, pp 447–456 | Cite as

Scheduling with due date assignment under special conditions on job processing

  • Valery Gordon
  • Vitaly StrusevichEmail author
  • Alexandre Dolgui
Article

Abstract

We review the results on scheduling with due date assignment under such conditions on job processing as given precedence constraints, maintenance activity or various scenarios of processing time changing. The due date assignment and scheduling problems arise in production planning when the management is faced with setting realistic due dates for a number of jobs. Most research on scheduling with due date assignment is focused on optimal sequencing of independent jobs. However, it is often found in practice that some products are manufactured in a certain order implied, for example, by technological, marketing or assembly requirements and this can be modeled by imposing precedence constraints on the set of jobs. In classical deterministic scheduling models, the processing conditions, including job processing times, are usually viewed as given constants. In many real-life situations, however, the processing conditions may vary over time, thereby affecting actual durations of jobs. In the models with controllable processing times, the scheduler can speed up job execution times by allocating some additional resources to the jobs. In the models with deterioration or learning, the actual processing time can depend either on the position or on the start time of a job in the schedule. In scheduling with deterioration, the later a job starts, the longer it takes to process, while in scheduling with learning, the actual processing time of a job gets shorter, provided that the job is scheduled later. We consider also scheduling models with optional maintenance activity. In manufacturing processing, production scheduling with preventive maintenance planning is one of the most significant methods in preventing the machinery from failure or wear.

Keywords

Scheduling Due date assignment Precedence constraints Deterioration Learning Maintenance activity 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Valery Gordon
  • Vitaly Strusevich
    • 1
    Email author
  • Alexandre Dolgui
    • 2
  1. 1.School of Computing and Mathematical Sciences, Old Royal Naval CollegeUniversity of GreenwichLondonUK
  2. 2.Industrial Engineering and Computer Science CentreEcole des Mines de Saint EtienneSaint Etienne Cedex 2France

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