A genetic algorithm for dynamic advanced planning and scheduling (DAPS) with a frozen interval
Expert Systems with Applications: An International Journal
Ant colony intelligence in multi-agent dynamic manufacturing scheduling
Engineering Applications of Artificial Intelligence
Approximation algorithms for multi-agent scheduling to minimize total weighted completion time
Information Processing Letters
Cross-layer rate control and dynamic scheduling in mobile ad hoc networks
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Setting a common due date in a constrained flowshop: A variable neighbourhood search approach
Computers and Operations Research
A priori parallel machines scheduling
Computers and Industrial Engineering
Competitive Two-Agent Scheduling and Its Applications
Operations Research
Rescheduling for Job Unavailability
Operations Research
The complexity of machine scheduling for stability with a single disrupted job
Operations Research Letters
Single-machine multi-agent scheduling problems with a global objective function
Journal of Scheduling
Pheromone-based coordination for manufacturing system control
Journal of Intelligent Manufacturing
Two-Agent scheduling on an unbounded serial batching machine
ISCO'12 Proceedings of the Second international conference on Combinatorial Optimization
Load balancing a priori strategy for the probabilistic weighted flowtime problem
Computers and Industrial Engineering
Reallocation problems in scheduling
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
International Journal of Intelligent Engineering Informatics
On the identical parallel-machine rescheduling with job rework disruption
Computers and Industrial Engineering
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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.