References
- Oduguwa, V.; Roy, R. A review of rolling system design optimisation. Int. J. Mach. Tools Manuf. 2006, 46, 912–928. DOI: 10.1016/j.ijmachtools.2005.07.023.
- Moslemipour, G.; Lee, T.; Rilling, D. A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems. Int. J. Adv. Manuf. Technol. 2012, 60, 11–27. DOI: 10.1007/s00170-011-3614-x.
- Sekulic, M.; Pejic, V.; Brezocnik, M.; Gostimirovic, M.; Hadzistevic, M. Prediction of surface roughness in the ball-end milling process using response surface methodology, genetic algorithms, and grey wolf optimizer algorithm. Adv. Produc. Engineer. Manag. 2018, 13, 18–30. DOI: 10.1016/j.ijmachtools.2005.07.023.
- Gusel, L.; Boskovic, V.; Domitner, J.; Ficko, M.; Brezocnik, M. Genetic programming method for modelling of cup height in deep drawing process. Adv. Produc. Engineer. Manag. 2018, 13, 358–365. DOI: 10.14743/apem2018.3.296.
- Kovacic, M.; Brezocnik, M. Reduction of surface defects and optimization of continuous casting of 70 mnvs4 Steel. Int. J. Simul. Model. 2018, 17, 667–676. DOI: 10.2507/IJSIMM17(4)457.
- Kovačič, M.; Rožej, U.; Brezočnik, M. Genetic algorithm rolling mill layout optimization. Mater. Manuf. Process. 2013, 28, 783–787. DOI: 10.1080/10426914.2012.718475.
- Furlan, M.; Almada-Lobo, B.; Santos, M.; Morabito, R. Unequal individual genetic algorithm with intelligent diversification for the lot-scheduling problem in integrated mills using multiple-paper machines. Comput. Oper. Res. 2015, 59, 33–50. DOI: 10.1016/j.cor.2014.12.008.
- Yang, J.; Wang, B.; Zou, C.; Li, X.; Li, T.; Liu, Q. Optimal charge planning model of steelmaking based on multi-objective evolutionary algorithm. Metals. 2018, 8, 1–12. DOI: 10.3390/met8070483.
- Eremeev, A.; Kovalenko, Y. V. Optimal recombination in genetic algorithms for combinatorial optimization problems - part II. Yugosl. J. Oper. Res. 2014, 24, 1–20. DOI: 10.2298/YJOR131030041E.
- Aksenov, S. A.; Chumachenko, E. N.; Logashina, I. V.; Kubina, T. Numerical Simulation in Roll Pass Design for Bar Rolling. Metalurgija. 2015, 54, 75–78.
- Huang, B.; Xing, K.; Abhary, K.; Spuzic, S. Optimization of oval–round pass design using genetic algorithm. Robot. Comput. Integr. Manuf. 2012, 28, 493–499. DOI: 10.1016/j.rcim.2012.02.004.
- García-Hernández, L.; Arauzo-Azofra, A.; Salas-Morera, L.; Pierreval, H.; Corchado, E. Facility Layout design using a multi-objective interactive genetic algorithm to support the DM. Expert Syst. 2015, 32, 94–107. DOI: 10.1111/exsy.12064.
- Nalawadw, R. S.; Marje, V. R.; Balachandran, G.; Balasubramanian, V. Effect of pass schedule and groove design on the metal deformation of 38 mnvs6 in the initial passes of hot rolling. Sadhana. 2016, 41, 111–124. DOI: 10.1007/s12046-015-0457-4.
- Gračnar, A. Optimizacija Razmestitve Kaliber in Pripadajočih Dovodnih Skrinj Za Valjanje Okroglih Jeklenih Profilov Z Uporabo Genetskega Algoritma. Master thesis, (in Slovene), University of Maribor, Faculty of Mechanical Engineering, Slovenia, 2016.