How to cite this paper
Sharma, N., Chawla, V & Ram, N. (2020). Comparison of machine learning algorithms for the automatic programming of computer numerical control machine.International Journal of Data and Network Science, 4(1), 1-14.
Refrences
Agarwalla, N., Panda, D., & Modi, M. K. (2016). Deep learning using restricted boltzmann machines. International Journal of Computational Intelligence and Information Security, 7(3), 1552-1556.
Amaitik, S. M., & Kiliç, S. E. (2007). An intelligent process planning system for prismatic parts using STEP features. The International Journal of Advanced Manufacturing Technology, 31(9-10), 978-993.
Angra, S., Chanda, A., & Chawla, V. (2018). Comparison and evaluation of job selection dispatching rules for integrated scheduling of multi-load automatic guided vehicles serving in variable-sized flexible manufacturing system layouts: A simulation study. Management Science Letters, 8(4), 187-200.
Balavignesh G, Kumaresan P, Kavitha.B.R, Ramya Govindaraj, Venkatesan.S (2017). Computer nu-merical control machine based on machine learning. International Journal of Pure and Applied Mathematics, 116(24), 521-527.
Balic.J., Kovacic. M., & Vaupotic.B., (2006). Intelligent programming of CNC turning operations us-ing a genetic algorithm. Journal of intelligent manufacturing, 7(3), 331-340.
Chanda, A., Angra, S., & Chawla, V. (2018). A modified memetic particle swarm optimization algo-rithm for sustainable multi-objective scheduling of automatic guided vehicles in a flexible manu-facturing system. International Journal of Computer-Aided Manufacturing, 4(1), 33-47.
Chawla, V. K., Chanda, A. K., & Angra, S. (2017). Evaluation of Dispatching Rules for Integrated Scheduling of AGVs in FMS. In National Conference on Recent Advances in Mechanical Engi-neering.
Chawla, V. K., Chanda, A. K., Angra, S. & Rani, S., (2018a). Simultaneous dispatching and schedul-ing of multi-load AGVs in FMS-A simulation study. Materials Today: Proceedings, 5(11), 25358-25367.
Chawla, V. K., Chanda, A. K., & Angra, S. (2018b). Multi-load AGVs scheduling by application of modified memetic particle swarm optimization algorithm. Journal of the Brazilian Society of Me-chanical Sciences and Engineering, 40(9), 436.
Chawla, V., Chanda, A., & Angra, S. (2018c). Sustainable multi-objective scheduling for automatic guided vehicle and flexible manufacturing system by a grey wolf optimization algorithm. Interna-tional Journal of Data and Network Science, 2(1), 27-40.
Chawla, V., Chanda, A., Angra, S., & Chawla, G. (2018d). The sustainable project management: A re-view and future possibilities. Journal of Project Management, 3(3), 157-170.
Chawla, V. K., Chanda, A. K., & Angra, S. (2019a). A clonal selection algorithm for minimizing dis-tance travel and back tracking of automatic guided vehicles in flexible manufacturing system. Journal of The Institution of Engineers (India): Series C, 100(3), 401-410.
Chawla, V., Chanda, A., & Angra, S. (2019b). The scheduling of automatic guided vehicles for the workload balancing and travel time minimization in the flexible manufacturing system by the na-ture-inspired algorithm. Journal of Project Management, 4(1), 19-30.
Chawla, V., Chanda, A., & Angra, S. (2019c). Material handling robots fleet size optimization by a heuristic. Journal of Project Management, 4(3), 177-184.
Chawla, V. K., Chanda, A. K., & Angra, S. (2019d). Simultaneous workload balancing and travel time minimization of automatic guided vehicles. In Journal of Physics: Conference Series, 1240(1), 012001. IOP Publishing.
Chawla, V. K., Chanda, A. K., Angra, S., & Rani, S. (2019e). Effect of nature-inspired algorithms and hybrid dispatching rules on the performance of automatic guided vehicles in the flexible manufac-turing system. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(10), 391.
Chitsaart.C., Rianmora, S., Rattana-Areeyagon, M., & Namjaiprasert, W. (2013). Automatic generat-ing CNC-code for milling machine. International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 7, 1519-1525.
Deb, S., Ghosh, K., & Paul, S. (2006). A neural network-based methodology for machining operations selection in computer-aided process planning for rotationally symmetrical parts. Journal of Intelli-gent Manufacturing, 17(5), 557-569.
Kilickap, E., Huseyinoglu, M., & Yardimeden, A. (2011). Optimization of drilling parameters on sur-face roughness in the drilling of AISI 1045 using response surface methodology and genetic algo-rithm. The International Journal of Advanced Manufacturing Technology, 52(1-4), 79-88.
Klancnik.S., Brezocnik, M., Balic, J., & Karabegovic.I. (2013). Programming of CNC milling ma-chines using particle swarm optimization. Materials and Manufacturing Processes, 28(7), 811-815.
Klancnik, S., Brezocnik, M., & Balic, J. (2016). Intelligent CAD/CAM system for programming of CNC machine tools. International Journal of Simulation & Modelling, 15(1), 109-120.
Moghaddam, B. F., Ruiz, R., & Sadjadi, S. J. (2012). Vehicle routing problem with uncertain de-mands: An advanced particle swarm algorithm. Computers & Industrial Engineering, 62(1), 306-317.
Onwubolu, G. C., & Clerc, M. (2004). The optimal path for automated drilling operations by a new heuristic approach using particle swarm optimization. International Journal of Production Re-search, 42(3), 473-491.
Preiss, K., & Kaplansky, E. (1985). Automated part programming for CNC milling by artificial intel-ligence techniques. Journal of Manufacturing Systems, 4(1), 51-63.
Rao, S. S., Satyanarayana, B., & Sarcar, M. M. M. (2012). Automated generation of NC part programs for turned parts based on 2-D drawing image files. International Journal of Production Re-search, 50(12), 3470-3485.
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Ed-ucation Limited.
Sadjadi, S. J., & Makui, A. (2002). An algorithm to compute the complexity of a static production planning (RESEARCH NOTE). International Journal of Engineering-Transactions A: Basics, 16(1), 57-60.
Sadrabadi, M. R., & Sadjadi, S. J. (2009). A new approach to solving multiple objective programming problems. International Journal of Industrial Engineering & Production Research, 20(1), 41-51.
Tiwari, R. K. (2013), Multi-objective optimization of drilling process variables using genetic algo-rithm for precision drilling operation. International Journal of Engineering Research and Devel-opment, 6(12), 43-59.
Tsagaris, A., Sagris, D., & Mansour, G. (2012). Intelligent CAD-based system for CNC machine con-trolling by genetic algorithms. 2012 IEEE 16th International Conference on Intelligent Engineer-ing Systems (INES) (pp. 235-239).
Warwick, K. (2013). Artificial intelligence: the basics. Routledge.
Amaitik, S. M., & Kiliç, S. E. (2007). An intelligent process planning system for prismatic parts using STEP features. The International Journal of Advanced Manufacturing Technology, 31(9-10), 978-993.
Angra, S., Chanda, A., & Chawla, V. (2018). Comparison and evaluation of job selection dispatching rules for integrated scheduling of multi-load automatic guided vehicles serving in variable-sized flexible manufacturing system layouts: A simulation study. Management Science Letters, 8(4), 187-200.
Balavignesh G, Kumaresan P, Kavitha.B.R, Ramya Govindaraj, Venkatesan.S (2017). Computer nu-merical control machine based on machine learning. International Journal of Pure and Applied Mathematics, 116(24), 521-527.
Balic.J., Kovacic. M., & Vaupotic.B., (2006). Intelligent programming of CNC turning operations us-ing a genetic algorithm. Journal of intelligent manufacturing, 7(3), 331-340.
Chanda, A., Angra, S., & Chawla, V. (2018). A modified memetic particle swarm optimization algo-rithm for sustainable multi-objective scheduling of automatic guided vehicles in a flexible manu-facturing system. International Journal of Computer-Aided Manufacturing, 4(1), 33-47.
Chawla, V. K., Chanda, A. K., & Angra, S. (2017). Evaluation of Dispatching Rules for Integrated Scheduling of AGVs in FMS. In National Conference on Recent Advances in Mechanical Engi-neering.
Chawla, V. K., Chanda, A. K., Angra, S. & Rani, S., (2018a). Simultaneous dispatching and schedul-ing of multi-load AGVs in FMS-A simulation study. Materials Today: Proceedings, 5(11), 25358-25367.
Chawla, V. K., Chanda, A. K., & Angra, S. (2018b). Multi-load AGVs scheduling by application of modified memetic particle swarm optimization algorithm. Journal of the Brazilian Society of Me-chanical Sciences and Engineering, 40(9), 436.
Chawla, V., Chanda, A., & Angra, S. (2018c). Sustainable multi-objective scheduling for automatic guided vehicle and flexible manufacturing system by a grey wolf optimization algorithm. Interna-tional Journal of Data and Network Science, 2(1), 27-40.
Chawla, V., Chanda, A., Angra, S., & Chawla, G. (2018d). The sustainable project management: A re-view and future possibilities. Journal of Project Management, 3(3), 157-170.
Chawla, V. K., Chanda, A. K., & Angra, S. (2019a). A clonal selection algorithm for minimizing dis-tance travel and back tracking of automatic guided vehicles in flexible manufacturing system. Journal of The Institution of Engineers (India): Series C, 100(3), 401-410.
Chawla, V., Chanda, A., & Angra, S. (2019b). The scheduling of automatic guided vehicles for the workload balancing and travel time minimization in the flexible manufacturing system by the na-ture-inspired algorithm. Journal of Project Management, 4(1), 19-30.
Chawla, V., Chanda, A., & Angra, S. (2019c). Material handling robots fleet size optimization by a heuristic. Journal of Project Management, 4(3), 177-184.
Chawla, V. K., Chanda, A. K., & Angra, S. (2019d). Simultaneous workload balancing and travel time minimization of automatic guided vehicles. In Journal of Physics: Conference Series, 1240(1), 012001. IOP Publishing.
Chawla, V. K., Chanda, A. K., Angra, S., & Rani, S. (2019e). Effect of nature-inspired algorithms and hybrid dispatching rules on the performance of automatic guided vehicles in the flexible manufac-turing system. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(10), 391.
Chitsaart.C., Rianmora, S., Rattana-Areeyagon, M., & Namjaiprasert, W. (2013). Automatic generat-ing CNC-code for milling machine. International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 7, 1519-1525.
Deb, S., Ghosh, K., & Paul, S. (2006). A neural network-based methodology for machining operations selection in computer-aided process planning for rotationally symmetrical parts. Journal of Intelli-gent Manufacturing, 17(5), 557-569.
Kilickap, E., Huseyinoglu, M., & Yardimeden, A. (2011). Optimization of drilling parameters on sur-face roughness in the drilling of AISI 1045 using response surface methodology and genetic algo-rithm. The International Journal of Advanced Manufacturing Technology, 52(1-4), 79-88.
Klancnik.S., Brezocnik, M., Balic, J., & Karabegovic.I. (2013). Programming of CNC milling ma-chines using particle swarm optimization. Materials and Manufacturing Processes, 28(7), 811-815.
Klancnik, S., Brezocnik, M., & Balic, J. (2016). Intelligent CAD/CAM system for programming of CNC machine tools. International Journal of Simulation & Modelling, 15(1), 109-120.
Moghaddam, B. F., Ruiz, R., & Sadjadi, S. J. (2012). Vehicle routing problem with uncertain de-mands: An advanced particle swarm algorithm. Computers & Industrial Engineering, 62(1), 306-317.
Onwubolu, G. C., & Clerc, M. (2004). The optimal path for automated drilling operations by a new heuristic approach using particle swarm optimization. International Journal of Production Re-search, 42(3), 473-491.
Preiss, K., & Kaplansky, E. (1985). Automated part programming for CNC milling by artificial intel-ligence techniques. Journal of Manufacturing Systems, 4(1), 51-63.
Rao, S. S., Satyanarayana, B., & Sarcar, M. M. M. (2012). Automated generation of NC part programs for turned parts based on 2-D drawing image files. International Journal of Production Re-search, 50(12), 3470-3485.
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Ed-ucation Limited.
Sadjadi, S. J., & Makui, A. (2002). An algorithm to compute the complexity of a static production planning (RESEARCH NOTE). International Journal of Engineering-Transactions A: Basics, 16(1), 57-60.
Sadrabadi, M. R., & Sadjadi, S. J. (2009). A new approach to solving multiple objective programming problems. International Journal of Industrial Engineering & Production Research, 20(1), 41-51.
Tiwari, R. K. (2013), Multi-objective optimization of drilling process variables using genetic algo-rithm for precision drilling operation. International Journal of Engineering Research and Devel-opment, 6(12), 43-59.
Tsagaris, A., Sagris, D., & Mansour, G. (2012). Intelligent CAD-based system for CNC machine con-trolling by genetic algorithms. 2012 IEEE 16th International Conference on Intelligent Engineer-ing Systems (INES) (pp. 235-239).
Warwick, K. (2013). Artificial intelligence: the basics. Routledge.