Scheduling with due date assignment under special conditions on job processing

Abstract

International audienceWe 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

Multitasking scheduling with batch distribution and due date assignment

“…This kind of scheduling problems is referred to scheduling with DDA or due window assignment in the literature, which has been extensively studied in the area of just-in-time scheduling and has been receiving widespread attention during the past four decades. The literature on this topic is abound, the interested readers are referred to the review papers by Gordon et al [9,10], and Kaminsky and Hochbaum [11]. Nevertheless, in contrast to our study, all the aforementioned studies as well as the review papers concentrate only on the problem of how to process the jobs while neglecting the problem of scheduling job delivery.…”

A mobile application for knowledge-enriched short-term scheduling of complex products

“…Moreover, the calculation of due dates in ETO environments is relatively mistreated. Most studies focus on static problem instances where jobs do not arrive continuously in the system [46], or require significant modelling efforts [53] and simulation experiments [54], which are rarely feasible in actual daily practice for due-date calculation.…”

Increasing accuracy and robustness of order promises

“…Cheng and Gupta (1989), Kaminsky and Hochbaum (2004), Gordon, Strusevich, and Dolgui (2012) and Janiak et al (2015) provide excellent reviews on due date assignment and scheduling. This stream of literature mainly focuses on approaches that schedule a given or uncertain amount of production orders on production resources on the shop floor level.…”