How to cite this paper
Debroy, A & Chakraborty, S. (2013). Non-conventional optimization techniques in optimizing non-traditional machining processes: A review.Management Science Letters , 3(1), 23-38.
Refrences
Ali-Tavoli, M., Nariman-Zadeh, N., Khakhali, A. & Mehran, M. (2007). Multi-objective optimization of abrasive flow machining processes using polynomial neural networks and genetic algorithms. Machining Science and Technology, 10, 491-510.
Amini, H., Soleymani Yazdi, M.R. & Dehghan. (2011). Optimization of process parameters in wire electrical discharge machining of TiB2 nano-composite ceramic. Journal of Engineering Manufacturing, 225(12), 2220-2227.
Bharti, P.S., Maheshwari, S. & Sharma, C. (2012). Multi-objective optimization of electric-discharge machining process using controlled elitist NSGA-II. Journal of Mechanical Science and Technology, 26(6), 1875-1883.
Chakravarthy, P.S. & Rarnesh Babu, N. (1999). A new approach for selection of optimal process parameters in abrasive water jet cutting. Materials and Manufacturing Processes, 14(4), 581-600.
Chakravarthy, P.S. & Rarnesh Babu, N. (2000). A hybrid approach for selection of optimal process parameters in abrasive water jet cutting. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 214(9), 781-791.
Chandrasekaran, M., Muralidhar, M., Murali Krishna, C. & Dixit, U.S. (2010). Application of soft computing techniques in machining performance prediction and optimization: A literature review. International Journal of Advanced Manufacturing Technology, 46, 445-464.
Chen, H-C., Lin, J-C., Yang, Y-K. & Tsai, C-H. (2010). Optimization of wire electrical discharge machining for pure tungsten using a neural network integrated simulated annealing approach. Expert Systems with Applications, 37, 7147-7153.
Ciurana, J., Arias, G. & Ozel, T. (2009). Neural network modeling and particle swarm optimization (PSO) of process parameters in pulsed laser micromachining of hardened AISI H13 steel. Materials and Manufacturing Processes, 24(3), 358-368.
Datta, D. & Das, A.K. (2010). Tuning process parameters of electrochemical machining using a multi-objective genetic algorithm: A preliminary study. In Lecture notes in Computer Science, Deb, K. et al. (Eds.) Springer-Verlag Berlin Heidelberg, 485-493.
Fenggou, C. & Dayong, Y. (2004). The study of high efficiency and intelligent optimization system in EDM sinking process. Journal of Materials Processing Technology, 149, 83-87.
Gao, Q., Zhang, Q-H., Su, S-P. & Zhang, J-H. (2008). Parameter optimization model in electrical discharge machining process. Journal of Zhejiang University Science A, 9(1), 104-108.
Golshan, A., Gohari, S. & Ayob, A. (2011a). Computational intelligence in optimization of wire electrical discharge machining of cold-work steel 2601. International Journal of Mechanical & Mechatronics Engineering, 11(4) 14-19.
Golshan, A., Gohari, S. & Ayob, A. (2011b). Comparison of intelligent optimization algorithms for wire electrical discharge machining parameters. Proc. of 3rd International Conference on Computational Intelligence, Modelling & Simulation, Malaysia, 134-140.
Jain, N.K., Jain, V.K. & Deb, K. (2007). Optimization of process parameters of mechanical type advanced machining processes using genetic algorithms. International Journal of Machine Tools & Manufacture, 47(6), 900-919.
Jain, N.K., Jain, V.K. & Jha, S. (2007). Parametric optimization of advanced fine-finishing processes. International Journal of Advanced Manufacturing Technology, 34, 1191-1213.
Jain, N.K. & Jain, V.K. (2012). Optimization of electro-chemical machining process parameters using genetic algorithms. Machining Science and Technology, 11(2), 235-258.
Joshi, S.N. & Pande, S.S. (2011). Intelligent process modeling and optimization of die-sinking electric discharge machining. Applied Soft Computing, 11, 2743-2755.
Kanagarajan, D., Karthikeyan, R., Palanikumar, K. & Davim, J.P. (2008). Optimization of electrical discharge machining characteristics of WC/Co composites using non-dominated sorting genetic algorithm (NSGA-II). International Journal of Advanced Manufacturing Technology, 36, 1124-1132.
Kolahan, F. & Bironro, M. (2008). Modeling and optimization of process parameters in PMEDM by genetic algorithm. World Academy of Science, Engineering and Technology, 48, 480-484.
Kondayya, D. & Gopala Krishna, A. (2011). An integrated evolutionary approach for modelling and optimization of wire electrical discharge machining. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 225(4), 549-567.
Kumar, K. & Agarwal, S. (2011). Multi-objective parametric optimization on machining with wire electric discharge machining. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-011-3833-1
Kuriakose, S. & Shunmugam, M.S. (2005). Multi-objective optimization of wire-electro discharge machining process by non-dominated sorting genetic algorithm. Journal of Materials Processing Technology, 170, 133-141.
Kuruvila, N. & Ravindra, H.V. (2011). Parametric influence and optimization of wire EDM of hot die steel. Machining Science and Technology, 15(1), 47-75.
Mahapatra, S.S. & Patnaik, A. (2006). Optimization of wire electrical discharge machining (WEDM) process parameters using genetic algorithm. Indian Journal of Engineering & Materials Sciences, 13, 494-502.
Maji, K. & Pratihar, D.K. (2011). Modeling of electrical discharge machining process using conventional regression analysis and genetic algorithms. Journal of Materials Engineering and Performance, 20, 1121-1127.
Majumder, A. (2012). Parametric optimization of electric discharge machining by GA-based response surface methodology. Journal for Manufacturing Science and Production, 12, 25-30.
Mandal, D., Pal, S.K. & Saha, P. (2007). Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II. Journal of Materials Processing Technology, 186, 154-162.
Mukherjee, R. & Chakraborty, S. (2012). Selection of the optimal electrochemical machining process parameters using biogeography-based optimization algorithm. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-012-4060-0.
Mukherjee, R. & Chakraborty, S. (2012). Selection of EDM process parameters using biogeography-based optimization algorithm. Materials and Manufacturing Processes, 27, 954-962.
Mukherjee, R., Chakraborty, S. & Samanta, S. (2012). Selection of wire electrical discharge machining process parameters using non-traditional optimization algorithms. Applied Soft Computing, 12, 2506-2516.
Nejad, R.A.M. (2011). Modeling and optimization of electrical discharge machining of SiC parameters, using neural network and non-dominating sorting genetic algorithm (NSGA II), Materials Sciences and Applications, 2, 669-675.
Padhee, S., Nayak, N., Panda, S.K., Dhal, P.R. & Mahapatra, S.S. (2012). Multi-objective parametric optimization of powder mixed electro-discharge machining using response surface methodology and non-dominated sorting genetic algorithm. Sadhana, 37(2), 223-240.
Rao, G.K.M., Rangajanardhaa, G., Rao, D.H. & Rao, M.S. (2009). Development of hybrid model and optimization of surface roughness in electric discharge machining using artificial neural networks and genetic algorithm. Journal of Materials Processing Technology, 209, 1512-1520.
Rao, R.V., Pawar, P.J. & Shankar, R. (2008). Multi-objective optimization of electrochemical machining process parameters using a particle swarm optimization algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 222(8), 949-958.
Rao, R.V. & Pawar, P.J. (2009). Modelling and optimization of process parameters of wire electrical discharge machining. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 223(11), 1431-1440.
Rao, R.V., Pawar, P.J. & Davim, J.P. (2010). Parameter optimization of ultrasonic machining process using nontraditional optimization algorithms. Materials and Manufacturing Processes, 25(10), 1120-1130.
Rao, R.V. & Kalyankar, V.D. (2012). Parameter optimization of modern machining processes using teaching-learning-based optimization algorithm. Engineering Applications of Artificial Intelligence, doi: 10.1016/j.engappai.2012.06.007.
Salman, ?. & Kayacan, M.C. (2008). Evolutionary programming method for modeling the EDM parameters for roughness. Journal of Materials Processing Technology, 200, 347-355.
Samanta, S. & Chakraborty, S. (2011). Parametric optimization of some non-traditional machining processes using artificial bee colony algorithm. Engineering Applications of Artificial Intelligence, 24(6), 946-957.
Sen, M. & Shan, H.S. (2006). Optimal selection of machining conditions in the electrojet drilling process using hybrid NN-DF-GA approach. Materials and Manufacturing Processes, 21, 349-356.
Sen, M. & Shan, H.S. (2007). Electro jet drilling using hybrid NNGA approach. Robotics and Computer-Integrated Manufacturing, 23, 17-24.
Senthilkumar, C., Ganesan, G. & Karthikeyan, R. (2010). Bi-performance optimization of electrochemical machining characteristics of Al/20%SiCp composites using NSGA-II. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 224(9), 1399-1407.
Senthilkumar, C., Ganesan, G. & Karthikeyan, R. (2011). Parametric optimization of electrochemical machining of Al/15% SiCp composites using NSGA-II. Transactions of Nonferrous Metals Society of China, 21, 2294-2300.
Somashekhar, K.P., Ramachandran, N. & Mathew, J. (2010). Optimization of material removal rate in micro-EDM using artificial neural network and genetic algorithms. Materials and Manufacturing Processes, 25, 467-475.
Somashekhar, K.P., Mathew, J. & Ramachandran, N. (2012). A feasibility approach by simulated annealing on optimization of micro-wire electric discharge machining parameters. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-012-4096-1.
Srinivasu, D.S. & Ramesh Babu, N. (2008). A neuro-genetic approach for selection of process parameters in abrasive waterjet cutting considering variation in diameter of focusing nozzle. Applied Soft Computing, 8, 809-819.
Su, J.C., Kao, J.Y. & Tarng, Y.S. (2004). Optimisation of the electrical discharge machining process using a GA-based neural network. International Journal of Advanced Manufacturing Technology, 24, 81-90.
Tarng. Y.S., Ma, S.C. & Chung, L.K. (1995). Determination of optimal cutting parameters in wire electrical discharge machining. International Journal of Machine Tools & Manufacture, 35(12), 1693-1701.
Yang, S-H., Srinivas, J., Mohan, S., Lee, D-M. & Balaji, S. (2009). Optimization of electric discharge machining using simulated annealing. Journal of Materials Processing Technology, 209, 4471-4475.
Yang, R.T., Tzeng, C.J., Yang, Y.K. & Hsieh, M.H. (2012). Optimization of wire electrical discharge machining process parameters for cutting tungsten. International Journal of Advanced Manufacturing Technology, 60, 135-147.
Yusup, N., Zain, A.M., Zaiton, S. & Hashim, M. (2012). Evolutionary techniques in optimizing machining parameters: Review and recent applications (2007-2011). Expert Systems with Applications, 39, 9909-9927.
Zain, A.M., Harona, H. & Sharif, S. (2011a). Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA. Expert Systems with Applications, 38, 8316-8326.
Zain, A.M., Haron, H. & Sharif, S. (2011b). Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA. Applied Soft Computing, 11, 5350-5359.
Zain, A.M., Haron, H. & Sharif, S. (2011c). Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining. Engineering with Computers, 27, 251-259.
Amini, H., Soleymani Yazdi, M.R. & Dehghan. (2011). Optimization of process parameters in wire electrical discharge machining of TiB2 nano-composite ceramic. Journal of Engineering Manufacturing, 225(12), 2220-2227.
Bharti, P.S., Maheshwari, S. & Sharma, C. (2012). Multi-objective optimization of electric-discharge machining process using controlled elitist NSGA-II. Journal of Mechanical Science and Technology, 26(6), 1875-1883.
Chakravarthy, P.S. & Rarnesh Babu, N. (1999). A new approach for selection of optimal process parameters in abrasive water jet cutting. Materials and Manufacturing Processes, 14(4), 581-600.
Chakravarthy, P.S. & Rarnesh Babu, N. (2000). A hybrid approach for selection of optimal process parameters in abrasive water jet cutting. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 214(9), 781-791.
Chandrasekaran, M., Muralidhar, M., Murali Krishna, C. & Dixit, U.S. (2010). Application of soft computing techniques in machining performance prediction and optimization: A literature review. International Journal of Advanced Manufacturing Technology, 46, 445-464.
Chen, H-C., Lin, J-C., Yang, Y-K. & Tsai, C-H. (2010). Optimization of wire electrical discharge machining for pure tungsten using a neural network integrated simulated annealing approach. Expert Systems with Applications, 37, 7147-7153.
Ciurana, J., Arias, G. & Ozel, T. (2009). Neural network modeling and particle swarm optimization (PSO) of process parameters in pulsed laser micromachining of hardened AISI H13 steel. Materials and Manufacturing Processes, 24(3), 358-368.
Datta, D. & Das, A.K. (2010). Tuning process parameters of electrochemical machining using a multi-objective genetic algorithm: A preliminary study. In Lecture notes in Computer Science, Deb, K. et al. (Eds.) Springer-Verlag Berlin Heidelberg, 485-493.
Fenggou, C. & Dayong, Y. (2004). The study of high efficiency and intelligent optimization system in EDM sinking process. Journal of Materials Processing Technology, 149, 83-87.
Gao, Q., Zhang, Q-H., Su, S-P. & Zhang, J-H. (2008). Parameter optimization model in electrical discharge machining process. Journal of Zhejiang University Science A, 9(1), 104-108.
Golshan, A., Gohari, S. & Ayob, A. (2011a). Computational intelligence in optimization of wire electrical discharge machining of cold-work steel 2601. International Journal of Mechanical & Mechatronics Engineering, 11(4) 14-19.
Golshan, A., Gohari, S. & Ayob, A. (2011b). Comparison of intelligent optimization algorithms for wire electrical discharge machining parameters. Proc. of 3rd International Conference on Computational Intelligence, Modelling & Simulation, Malaysia, 134-140.
Jain, N.K., Jain, V.K. & Deb, K. (2007). Optimization of process parameters of mechanical type advanced machining processes using genetic algorithms. International Journal of Machine Tools & Manufacture, 47(6), 900-919.
Jain, N.K., Jain, V.K. & Jha, S. (2007). Parametric optimization of advanced fine-finishing processes. International Journal of Advanced Manufacturing Technology, 34, 1191-1213.
Jain, N.K. & Jain, V.K. (2012). Optimization of electro-chemical machining process parameters using genetic algorithms. Machining Science and Technology, 11(2), 235-258.
Joshi, S.N. & Pande, S.S. (2011). Intelligent process modeling and optimization of die-sinking electric discharge machining. Applied Soft Computing, 11, 2743-2755.
Kanagarajan, D., Karthikeyan, R., Palanikumar, K. & Davim, J.P. (2008). Optimization of electrical discharge machining characteristics of WC/Co composites using non-dominated sorting genetic algorithm (NSGA-II). International Journal of Advanced Manufacturing Technology, 36, 1124-1132.
Kolahan, F. & Bironro, M. (2008). Modeling and optimization of process parameters in PMEDM by genetic algorithm. World Academy of Science, Engineering and Technology, 48, 480-484.
Kondayya, D. & Gopala Krishna, A. (2011). An integrated evolutionary approach for modelling and optimization of wire electrical discharge machining. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 225(4), 549-567.
Kumar, K. & Agarwal, S. (2011). Multi-objective parametric optimization on machining with wire electric discharge machining. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-011-3833-1
Kuriakose, S. & Shunmugam, M.S. (2005). Multi-objective optimization of wire-electro discharge machining process by non-dominated sorting genetic algorithm. Journal of Materials Processing Technology, 170, 133-141.
Kuruvila, N. & Ravindra, H.V. (2011). Parametric influence and optimization of wire EDM of hot die steel. Machining Science and Technology, 15(1), 47-75.
Mahapatra, S.S. & Patnaik, A. (2006). Optimization of wire electrical discharge machining (WEDM) process parameters using genetic algorithm. Indian Journal of Engineering & Materials Sciences, 13, 494-502.
Maji, K. & Pratihar, D.K. (2011). Modeling of electrical discharge machining process using conventional regression analysis and genetic algorithms. Journal of Materials Engineering and Performance, 20, 1121-1127.
Majumder, A. (2012). Parametric optimization of electric discharge machining by GA-based response surface methodology. Journal for Manufacturing Science and Production, 12, 25-30.
Mandal, D., Pal, S.K. & Saha, P. (2007). Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II. Journal of Materials Processing Technology, 186, 154-162.
Mukherjee, R. & Chakraborty, S. (2012). Selection of the optimal electrochemical machining process parameters using biogeography-based optimization algorithm. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-012-4060-0.
Mukherjee, R. & Chakraborty, S. (2012). Selection of EDM process parameters using biogeography-based optimization algorithm. Materials and Manufacturing Processes, 27, 954-962.
Mukherjee, R., Chakraborty, S. & Samanta, S. (2012). Selection of wire electrical discharge machining process parameters using non-traditional optimization algorithms. Applied Soft Computing, 12, 2506-2516.
Nejad, R.A.M. (2011). Modeling and optimization of electrical discharge machining of SiC parameters, using neural network and non-dominating sorting genetic algorithm (NSGA II), Materials Sciences and Applications, 2, 669-675.
Padhee, S., Nayak, N., Panda, S.K., Dhal, P.R. & Mahapatra, S.S. (2012). Multi-objective parametric optimization of powder mixed electro-discharge machining using response surface methodology and non-dominated sorting genetic algorithm. Sadhana, 37(2), 223-240.
Rao, G.K.M., Rangajanardhaa, G., Rao, D.H. & Rao, M.S. (2009). Development of hybrid model and optimization of surface roughness in electric discharge machining using artificial neural networks and genetic algorithm. Journal of Materials Processing Technology, 209, 1512-1520.
Rao, R.V., Pawar, P.J. & Shankar, R. (2008). Multi-objective optimization of electrochemical machining process parameters using a particle swarm optimization algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 222(8), 949-958.
Rao, R.V. & Pawar, P.J. (2009). Modelling and optimization of process parameters of wire electrical discharge machining. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 223(11), 1431-1440.
Rao, R.V., Pawar, P.J. & Davim, J.P. (2010). Parameter optimization of ultrasonic machining process using nontraditional optimization algorithms. Materials and Manufacturing Processes, 25(10), 1120-1130.
Rao, R.V. & Kalyankar, V.D. (2012). Parameter optimization of modern machining processes using teaching-learning-based optimization algorithm. Engineering Applications of Artificial Intelligence, doi: 10.1016/j.engappai.2012.06.007.
Salman, ?. & Kayacan, M.C. (2008). Evolutionary programming method for modeling the EDM parameters for roughness. Journal of Materials Processing Technology, 200, 347-355.
Samanta, S. & Chakraborty, S. (2011). Parametric optimization of some non-traditional machining processes using artificial bee colony algorithm. Engineering Applications of Artificial Intelligence, 24(6), 946-957.
Sen, M. & Shan, H.S. (2006). Optimal selection of machining conditions in the electrojet drilling process using hybrid NN-DF-GA approach. Materials and Manufacturing Processes, 21, 349-356.
Sen, M. & Shan, H.S. (2007). Electro jet drilling using hybrid NNGA approach. Robotics and Computer-Integrated Manufacturing, 23, 17-24.
Senthilkumar, C., Ganesan, G. & Karthikeyan, R. (2010). Bi-performance optimization of electrochemical machining characteristics of Al/20%SiCp composites using NSGA-II. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 224(9), 1399-1407.
Senthilkumar, C., Ganesan, G. & Karthikeyan, R. (2011). Parametric optimization of electrochemical machining of Al/15% SiCp composites using NSGA-II. Transactions of Nonferrous Metals Society of China, 21, 2294-2300.
Somashekhar, K.P., Ramachandran, N. & Mathew, J. (2010). Optimization of material removal rate in micro-EDM using artificial neural network and genetic algorithms. Materials and Manufacturing Processes, 25, 467-475.
Somashekhar, K.P., Mathew, J. & Ramachandran, N. (2012). A feasibility approach by simulated annealing on optimization of micro-wire electric discharge machining parameters. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-012-4096-1.
Srinivasu, D.S. & Ramesh Babu, N. (2008). A neuro-genetic approach for selection of process parameters in abrasive waterjet cutting considering variation in diameter of focusing nozzle. Applied Soft Computing, 8, 809-819.
Su, J.C., Kao, J.Y. & Tarng, Y.S. (2004). Optimisation of the electrical discharge machining process using a GA-based neural network. International Journal of Advanced Manufacturing Technology, 24, 81-90.
Tarng. Y.S., Ma, S.C. & Chung, L.K. (1995). Determination of optimal cutting parameters in wire electrical discharge machining. International Journal of Machine Tools & Manufacture, 35(12), 1693-1701.
Yang, S-H., Srinivas, J., Mohan, S., Lee, D-M. & Balaji, S. (2009). Optimization of electric discharge machining using simulated annealing. Journal of Materials Processing Technology, 209, 4471-4475.
Yang, R.T., Tzeng, C.J., Yang, Y.K. & Hsieh, M.H. (2012). Optimization of wire electrical discharge machining process parameters for cutting tungsten. International Journal of Advanced Manufacturing Technology, 60, 135-147.
Yusup, N., Zain, A.M., Zaiton, S. & Hashim, M. (2012). Evolutionary techniques in optimizing machining parameters: Review and recent applications (2007-2011). Expert Systems with Applications, 39, 9909-9927.
Zain, A.M., Harona, H. & Sharif, S. (2011a). Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA. Expert Systems with Applications, 38, 8316-8326.
Zain, A.M., Haron, H. & Sharif, S. (2011b). Optimization of process parameters in the abrasive waterjet machining using integrated SA-GA. Applied Soft Computing, 11, 5350-5359.
Zain, A.M., Haron, H. & Sharif, S. (2011c). Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining. Engineering with Computers, 27, 251-259.