Simplifying dispatching rules in genetic programming for dynamic job shop scheduling
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Publication:2163788
DOI10.1007/978-3-031-04148-8_7zbMath1499.90083OpenAlexW4226359091MaRDI QIDQ2163788
Sai Panda, Mengjie Zhang, Yi Mei
Publication date: 11 August 2022
Full work available at URL: https://doi.org/10.1007/978-3-031-04148-8_7
Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)
Cites Work
- Mathematical programming formulations for machine scheduling: A survey
- A branch and bound algorithm for the job-shop scheduling problem
- A comparative study of dispatching rules in dynamic flowshops and jobshops
- Some new results on simulated annealing applied to the job shop scheduling problem
- A cutting plane algorithm for the unrelated parallel machine scheduling problem
- Development and analysis of cost-based dispatching rules for job shop scheduling
- Applying tabu search to the job-shop scheduling problem
- A genetic algorithm for the flexible job-shop scheduling problem
- A hybrid genetic algorithm for the job shop scheduling problem
- Exploring Hyper-heuristic Methodologies with Genetic Programming
- EXPLICITLY SIMPLIFYING EVOLVED GENETIC PROGRAMS DURING EVOLUTION
- Job Shop Scheduling by Simulated Annealing
- Nurse Scheduling Using Mathematical Programming
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