Multi-objective spur gear design using teaching learning-based optimization and decision-making techniques

References

• Arora, R., Kaushik, S. C., & Kumar, R. (2017). Multi-objective thermodynamic optimisation of solar parabolic dish Stirling heat engine using NSGA-II and decision making. International Journal of Renewable Energy Technology, 8(1), 64–25. doi:10.1504/IJRET.2017.080873
   Google Scholar
• Arora, R., Kaushik, S. C., Kumar, R., & Arora, R. (2016a). ‘Soft computing based multi-objective optimization of Brayton cycle power plant with isothermal heat addition using evolutionary algorithm and decision making’. Applied Soft Computing, 46, 267–283. doi:10.1016/j.asoc.2016.05.001
   Web of Science ®Google Scholar
• Arora, R, Kaushik, S.C, & Kumar, R. (2016b). Multi-objective thermodynamic optimization of solar parabolic dish stirling heat engine with regenerative losses using nsga-ii and decision-making. Applied Solar Energy, 52(4), 295-304.
   Google Scholar
• Arora, R., Kaushik, S. C., Kumar, R., & Arora, R. (2016c). Multi-objective thermo- economic optimization of solar parabolic dish Stirling heat engine with regenerative losses using NSGA-II and decision making. International Journal of Electrical Power & Energy Systems, 74, 25–35.
   Web of Science ®Google Scholar
• Crepsinek, M., Liu, S., & Mernik, L. (2012). A note on teaching – Learning-based optimization algorithm. Information Sciences, 212, 79–93. doi:10.1016/j.ins.2012.05.009
   Web of Science ®Google Scholar
• Deb, K., & Jain, S. (2003). Multi-speed gearbox design using multi-objective evolutionary algorithms. Journal of Mechanical Design, 125(3), 609–619. doi:10.1115/1.1596242
   Web of Science ®Google Scholar
• Dörterler, M., Şahin, İ., & Gökçe, H. (2019). A grey wolf optimizer approach for optimal weight design problem of the spur gear. Engineering Optimization, 51(6), 1013–1027. doi:10.1080/0305215X.2018.1509963
   Web of Science ®Google Scholar
• Hofstetter, M., Lechleitner, D., Hirz, M., Gintzel, M., & Schmidhofer, A. (2018). Multi-objective gearbox design optimization for x{EV}-Axle drives under consideration of package restrictions. Dritev - Drivetrain for Vehicles. doi:10.1007/s10010-018-0278-9
   Google Scholar
• Kumar, R., Kaushik, S. C., Kumar, R., & Hans, R. (2016). Multi-objective thermodynamic optimization of an irreversible regenerative Brayton cycle using evolutionary algorithm and decision making. Ain Shams Engineering Journal, 7(2), 741–753. doi:10.1016/j.asej.2015.06.007
   Web of Science ®Google Scholar
• Li, S., Vaidyanathan, A., Harianto, J., & KAHRAMAN, A. (2009). Influence of design parameters on mechanical power losses of helical gear pairs. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 3(2), 146–158. doi:10.1299/jamdsm.3.146
   Web of Science ®Google Scholar
• Lin, W., Yu, D. Y., Wang, S., Zhang, C., Zhang, S., Tian, H., … Liu, S. (2015). Multi-objective teaching – Learning-based optimization algorithm for reducing carbon emissions and operation time in turning operations. Engineering Optimization, 47(7), 994–1007. doi:10.1080/0305215X.2014.928818
   Web of Science ®Google Scholar
• Maputi, E. S., & Arora, R. (2019). Design optimization of a three-stage transmission using advanced optimization techniques. International Journal of Simulation and Multidisciplinary Optimization, 10, A8. doi:10.1051/smdo/2019009
   Google Scholar
• Messac, A. (1996). Physical programming - Effective optimization for computational design. American Institute of Aeronautics and Astronautics Journal, 34(1), 149–158. doi:10.2514/3.13035
   Web of Science ®Google Scholar
• Messac, A. (2015). Optimization in practice with MATLAB®: For engineering students and professionals. Cambridge: University Press. Cambridge University Press.
   Google Scholar
• Miler, D., Žeželj, D., Lončar, A., & Vučković, K. (2018). Multi-objective spur gear pair optimization focused on volume and efficiency. Mechanism and Machine Theory, 125, 185–195. doi:10.1016/j.mechmachtheory.2018.03.012
   Web of Science ®Google Scholar
• Mogal, Y.K., & Wakchaure, V.D. (2013). A multi-objective optimization approach for design of worm and worm wheel based on genetic algorithm. Bonfring International Journal Of Man Machine Interface, 3(1), 8-12. doi: 10.9756/BIJMMI.14403
   Google Scholar
• Padmanabhan, S., Chandrasekaran, M., Asokan, P., & Raman, V. S. (2013). Optimal solution for gear drive design using population based algorithm. Young, 852, 852–864.
   Google Scholar
• Padmanabhan, S., Srinivasa Raman, V., & Chandrasekaran, M. (2014). Optimisation of gear reducer using evolutionary algorithm. Materials Research Innovations, 18, S6–378–83. doi:10.1179/1432891714Z.000000000983
   Google Scholar
• Patil, M., Ramkumar, P., & Krishnapallai, S. (2017). Multi-objective optimization of two stage spur gearbox using NSGA-II, “SAE Technical Paper 2017-28-1939. doi: 10.4271/2017-28-1939
   Google Scholar
• Petry-Johnson, T. T., Kahraman, A., Anderson, N. E., & Chase, D. R. (2008). An experimental investigation of spur gear efficiency. Journal of Mechanical Design, 130(6), 062601. doi:10.1115/1.2898876
   Web of Science ®Google Scholar
• Rai, P., Agrawal, A., Saini, M.L., Jodder, C. and Barman, A.G. (2018). Volume optimization of helical gear with profile shift using real coded genetic algorithm. Procedia Computer Science, Elsevier B.V. 133, 718–724. doi:10.1016/j.procs.2018.07.127
   Google Scholar
• Rao, R. V. (2016). Teaching learning based optimization algorithm. doi:10.1007/978-3-319-22732-0
   Google Scholar
• Rao, R. V., Savsani, V. J., & Balic, J. (2012). Teaching – Learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems. Engineering Optimization, 44(12), 1447–1462. doi:10.1080/0305215X.2011.652103
   Web of Science ®Google Scholar
• Sanghvi, R. C., et al. (2014). Multi-objective optimization of two-stage helical gear train using NSGA-II. Journal of Optimization, 2014, 8. doi:10.1155/2014/670297
   Google Scholar
• Savsani, V., Rao, R. V., & Vakharia, D. P. (2010). ‘Optimal weight design of a gear train using particle swarm optimization and simulated annealing algorithms’. Mechanism and Machine Theory, 45(3), Elsevier Ltd, 531–541. doi:10.1016/j.mechmachtheory.2009.10.010
   Web of Science ®Google Scholar
• Siegmund, F., Ng, A. H. C., & Deb, K. (2012). ‘Finding a preferred diverse set of Pareto-optimal solutions for a limited number of function calls’, 2012. IEEE Congress on Evolutionary Computation, CEC. doi:10.1109/CEC.2012.6256654
   Google Scholar
• Thompson, D. F., Gupta, S., & Shukla, A. (2000). Tradeoff analysis in minimum volume design of multi-stage spur gear reduction units. Mechanism and Machine Theory, 35(5), 609–627. doi:10.1016/S0094-114X(99)00036-1
   Web of Science ®Google Scholar
• Waghmare, G. (2013). Comments on “a note on teaching-learning-based optimization algorithm”. Information Sciences, 229(December), 159–169. doi:10.1016/j.ins.2012.11.009
   Web of Science ®Google Scholar
• Wang, C., Wang, S., & Wang, G. (2017). Volume models for different structures of spur gear. Australian Journal of Mechanical Engineering, Taylor & Francis, (October), 1–9. doi: 10.1080/14484846.2017.1381373
   Google Scholar
• Yokota, T., Taguchi, T., & Gen, M. (1998). A solution method for optimal weight design problem of the gear using genetic algorithms. Computers & Industrial Engineering, 35(3–4), 523–526. doi:10.1016/S0360-8352(98)00149-1
   Web of Science ®Google Scholar
• Zolfaghari, A., Goharimanesh, M., & Akbari, A. A. (2017). Optimum design of straight bevel gears pair using evolutionary algorithms. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 39(6), Springer Berlin Heidelberg, 2121–2129. doi:10.1007/s40430-017-0733-9
   Web of Science ®Google Scholar