Rescheduling for New Orders

Abstract

This paper considers scheduling problems where a set of original jobs has already been scheduled to minimize some cost objective, when a new set of jobs arrives and creates a disruption. The decision maker needs to insert the new jobs into the existing schedule without excessively disrupting it. Two classes of models are considered. First, we minimize the scheduling cost of all the jobs, subject to a limit on the disruption caused to the original schedule, where this disruption is measured in various ways. In the second class, a total cost objective, which includes both the original cost measure and the cost of disruption, is minimized. For both classes and various costs based on classical scheduling objectives, and for almost all problems, we provide either an efficient algorithm or a proof that such an algorithm is unlikely to exist. We also show how to extend both classes of models to deal with multiple disruptions in the form of repeated arrivals of new jobs. Our work refocuses the extensive literature on scheduling problems towards issues of rescheduling, which are important because of the frequency with which disruptions occur in manufacturing practice.

Pheromone-based Dynamic Coordination for Manufacturing System

“…Therefore, the task allocation can be looked as ants' food foraging process. Generally speaking, a task can be finished by several routes; in order to make each route have a chance to be selected, so at the beginning, we set an initial value for each route that has the ability to finish the given task, as shown in (2). (1).…”

“…The unforeseen disturbances include: the arrival of new orders, order cancellations, changes in order priority, processing delays, changes in release dates, machine breakdowns, etc. [1,2]. Hence, such dynamic manufacturing systems require dynamic coordination and control to make full use of system resources, and then improve the system performance.…”

Partitioning sequencing situations and games

“…The following algorithm, introduced by Hall and Potts (2004), establishes an optimal order of a partitioning sequencing situation. The algorithm is based on the Shortest Processing Time (SPT) rule.…”

“…We introduce the partitioning equal gain splitting rule (PEGS-rule). This rule is inspired on the algorithm of Hall and Potts (2004), that finds an optimal order for partitioning sequencing situations. Moreover, the PEGS-rule is characterised using efficiency, symmetry and consistency.…”

Single machine interfering jobs problem with flowtime objective

“…Multi-agent scheduling problems model many realistic situations in productive environments. In a recent review on the topic, Perez-Gonzalez and cite a number of real applications in di erent domains, such as supply chain scheduling (Fan, 2010), rescheduling (Unal et al, 1997;Perez-Gonzalez and Framinan, 2010;Hall and Potts, 2004;Mu and Gu, 2010), telecommunications (Peha and Tobagi, * This is an Accepted Manuscript of an article published by Springer in the Journal of Intelligent Manufacturing, http://dx.doi.org/10.1007/s10845-015-1141-6 (Khelifati and Bouzid-Sitayeb, 2011;Wan et al, 2010;Kellerer and Strusevich, 2010).…”