How to cite this paper
Bhunia, A., Pal, P & Chattopadhyay, S. (2015). A hybrid of genetic algorithm and Fletcher-Reeves for bound constrained optimization problems.Decision Science Letters , 4(2), 125-136.
Refrences
Baker, J. E. (1985, July). Adaptive selection methods for genetic algorithms. In Proceedings of an International Conference on Genetic Algorithms and their applications (pp. 101-111).
Bhunia, A., Pal, P., Chattopadhyay, S., & Medya, B. (2011). An inventory model of two-warehouse system with variable demand dependent on instantaneous displayed stock and marketing decisions via hybrid RCGA. International Journal of Industrial Engineering Computations, 2(2), 351-368.
Chelouah, R., & Siarry, P. (2000). A continuous genetic algorithm designed for the global optimization of multimodal functions. Journal of Heuristics, 6(2), 191-213.
Jana, R. K., & Biswal, M. P. (2004). Stochastic simulation-based genetic algorithm for chance constraint programming problems with continuous random variables. International Journal of Computer Mathematics, 81(9), 1069-1076.
Deb, K. (2000). An efficient constraint handling method for genetic algorithms. Computer methods in applied mechanics and engineering, 186(2), 311-338.
Deb, K., Anand, A., & Joshi, D. (2002). A computationally efficient evolutionary algorithm for real-parameter optimization. Evolutionary computation, 10(4), 371-395.
Deep, K., & Thakur, M. (2007). A new crossover operator for real coded genetic algorithms. Applied Mathematics and Computation, 188(1), 895-911.
Gen, M. & Cheng, R. (2000). Genetic Algorithms and Engineering Optimization. John Wiley & Sons Inc.
Goldberg, D. E. (1989). Genetic Algorithms: Search, Optimization and Machine Learning, Addison Wesley.
Holland, J. H. (1975). Adaptation of Natural and Artificial system, University of Michigan Press, Ann Arbor.
Ibrahim, M. A. H., Mamat, M., & Leong, W. J. (2014, March). The Hybrid BFGS-CG Method in Solving Unconstrained Optimization Problems. In Abstract and Applied Analysis (Vol. 2014). Hindawi Publishing Corporation.
Karaboga, D. & Basturk, B. (2008). On the performance of artificial bee colony (ABC) algorithm. Applied Soft Computing, 8 (1), 687–697.
Luo, Y. Z., Tang, G. J., & Zhou, L. N. (2008). Hybrid approach for solving systems of nonlinear equations using chaos optimization and quasi-Newton method. Applied Soft Computing, 8(2), 1068-1073.
Makinen, R.A.E., Periaux, J. & Toivanen, J. (1999). Multidisciplinary shape optimization in aerodynamics and electromagnetic using genetic algorithm, International Journal for Numerical Methods in Fluids, 30(2),149-159.
Miettinen, K., M?kel?, M. M., & Toivanen, J. (2003). Numerical comparison of some penalty-based constraint handling techniques in genetic algorithms. Journal of Global Optimization, 27(4), 427-446.
Michalawicz, Z. (1996). Genetic Algorithms + Data structure= Evaluation Programs. Springer Verlog, Berlin.
Mitchell, M. (1996). Introduction to Genetic Algorithms, PHI, New Delhi.
Pal, P., Das, B., Panda, A. & Bhunia, A. K. (2005). An application of real-coded genetic algorithm for mixed integer non-linear programming in an optimal two-warehouse inventory policy for deteriorating items with a linear trend in demand and a fixed planning horizon. International Journal of Computer Mathematics, 82(2), 167-175.
Rao, R. V. & Patel, V. (2012). An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems. International Journal of Industrial Engineering Computations, 3, 535–560.
Sakawa, M. (2002). Genetic Algorithms and fuzzy multiobjective optimization. USA: Kluwer Academic Publishers.
Yao, X., & Xu, Y. (2006). Recent Advances in Evolutionary Computation. Journal of Computer Science and Technology, 21(1), 1-18.
Yiu, K. F. C., Liu, Y., & Teo, K. L. (2004). A hybrid descent method for global optimization. Journal of Global Optimization, 28(2), 229-238.
Bhunia, A., Pal, P., Chattopadhyay, S., & Medya, B. (2011). An inventory model of two-warehouse system with variable demand dependent on instantaneous displayed stock and marketing decisions via hybrid RCGA. International Journal of Industrial Engineering Computations, 2(2), 351-368.
Chelouah, R., & Siarry, P. (2000). A continuous genetic algorithm designed for the global optimization of multimodal functions. Journal of Heuristics, 6(2), 191-213.
Jana, R. K., & Biswal, M. P. (2004). Stochastic simulation-based genetic algorithm for chance constraint programming problems with continuous random variables. International Journal of Computer Mathematics, 81(9), 1069-1076.
Deb, K. (2000). An efficient constraint handling method for genetic algorithms. Computer methods in applied mechanics and engineering, 186(2), 311-338.
Deb, K., Anand, A., & Joshi, D. (2002). A computationally efficient evolutionary algorithm for real-parameter optimization. Evolutionary computation, 10(4), 371-395.
Deep, K., & Thakur, M. (2007). A new crossover operator for real coded genetic algorithms. Applied Mathematics and Computation, 188(1), 895-911.
Gen, M. & Cheng, R. (2000). Genetic Algorithms and Engineering Optimization. John Wiley & Sons Inc.
Goldberg, D. E. (1989). Genetic Algorithms: Search, Optimization and Machine Learning, Addison Wesley.
Holland, J. H. (1975). Adaptation of Natural and Artificial system, University of Michigan Press, Ann Arbor.
Ibrahim, M. A. H., Mamat, M., & Leong, W. J. (2014, March). The Hybrid BFGS-CG Method in Solving Unconstrained Optimization Problems. In Abstract and Applied Analysis (Vol. 2014). Hindawi Publishing Corporation.
Karaboga, D. & Basturk, B. (2008). On the performance of artificial bee colony (ABC) algorithm. Applied Soft Computing, 8 (1), 687–697.
Luo, Y. Z., Tang, G. J., & Zhou, L. N. (2008). Hybrid approach for solving systems of nonlinear equations using chaos optimization and quasi-Newton method. Applied Soft Computing, 8(2), 1068-1073.
Makinen, R.A.E., Periaux, J. & Toivanen, J. (1999). Multidisciplinary shape optimization in aerodynamics and electromagnetic using genetic algorithm, International Journal for Numerical Methods in Fluids, 30(2),149-159.
Miettinen, K., M?kel?, M. M., & Toivanen, J. (2003). Numerical comparison of some penalty-based constraint handling techniques in genetic algorithms. Journal of Global Optimization, 27(4), 427-446.
Michalawicz, Z. (1996). Genetic Algorithms + Data structure= Evaluation Programs. Springer Verlog, Berlin.
Mitchell, M. (1996). Introduction to Genetic Algorithms, PHI, New Delhi.
Pal, P., Das, B., Panda, A. & Bhunia, A. K. (2005). An application of real-coded genetic algorithm for mixed integer non-linear programming in an optimal two-warehouse inventory policy for deteriorating items with a linear trend in demand and a fixed planning horizon. International Journal of Computer Mathematics, 82(2), 167-175.
Rao, R. V. & Patel, V. (2012). An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems. International Journal of Industrial Engineering Computations, 3, 535–560.
Sakawa, M. (2002). Genetic Algorithms and fuzzy multiobjective optimization. USA: Kluwer Academic Publishers.
Yao, X., & Xu, Y. (2006). Recent Advances in Evolutionary Computation. Journal of Computer Science and Technology, 21(1), 1-18.
Yiu, K. F. C., Liu, Y., & Teo, K. L. (2004). A hybrid descent method for global optimization. Journal of Global Optimization, 28(2), 229-238.