Evolving "less-myopic" scheduling rules for dynamic job shop scheduling with genetic programming
Author:
Affiliation:
1. Victoria University of Wellington, Wellington, New Zealand
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2576768.2598224
Reference26 articles.
1. Executing production schedules in the face of uncertainties: A review and some future directions
2. The job shop scheduling problem: Conventional and new solution techniques
3. Evolutionary search for difficult problem instances to support the design of job shop dispatching rules
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3. A Simulation Optimization-Aided Learning Method for Design Automation of Scheduling Rules;2022 IEEE 18th International Conference on Automation Science and Engineering (CASE);2022-08-20
4. Introduction to automated design of scheduling heuristics with genetic programming;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2022-07-09
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