Improvement heuristic for the flow-shop scheduling problem: An adaptive-learning approach
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- Kalczynski, Pawel J. & Kamburowski, Jerzy, 2009. "An empirical analysis of the optimality rate of flow shop heuristics," European Journal of Operational Research, Elsevier, vol. 198(1), pages 93-101, October.
- Swan, Jerry & Adriaensen, Steven & Brownlee, Alexander E.I. & Hammond, Kevin & Johnson, Colin G. & Kheiri, Ahmed & Krawiec, Faustyna & Merelo, J.J. & Minku, Leandro L. & Özcan, Ender & Pappa, Gisele L, 2022. "Metaheuristics “In the Large”," European Journal of Operational Research, Elsevier, vol. 297(2), pages 393-406.
- Brammer, Janis & Lutz, Bernhard & Neumann, Dirk, 2022. "Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 75-86.
- Martín Ravetti & Carlos Riveros & Alexandre Mendes & Mauricio Resende & Panos Pardalos, 2012. "Parallel hybrid heuristics for the permutation flow shop problem," Annals of Operations Research, Springer, vol. 199(1), pages 269-284, October.
- Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose M., 2017. "A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 707-721.
- Sinem Buyuksaatci Kiris & Enes Eryarsoy & Selim Zaim & Dursun Delen, 2023. "An integrated approach for lean production using simulation and data envelopment analysis," Annals of Operations Research, Springer, vol. 320(2), pages 863-886, January.
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