Optimization of a Reverse Osmosis System Using Genetic Algorithm

References

• Androulakis , I. P. and Venkatasubramanian , V. 1991 . A genetic algorithmic framework for process design and optimization . Computers and Chemical Engineering , 15 : 217 – 228 .
   Web of Science ®Google Scholar
• Fraga , E. S. and Senos Matias , T. R. 1996 . Synthesis and optimization of a nonideal distillation system using a parallel genetic algorithm . Computers and Chemical Engineering , 20 : S79 – S84 .
   Web of Science ®Google Scholar
• Garrard , A. and Fraga , E. S. 1998 . Mass exchange network synthesis using genetic algorithms . Computers and Chemical Engineering , 22 : 1837 – 1850 .
   Web of Science ®Google Scholar
• Deb , K. 1995 . Optimization for Engineering Design: Algorithms and Examples New Delhi : Prentice‐Hall .
   Google Scholar
• Srinivas , N. and Deb , K. 1994 . Multiobjective optimization using nondominated sorting in genetic algorithms . Evolutionary Computation , 2 : 221 – 248 .
   Web of Science ®Google Scholar
• Gupta , R. R. and Gupta , S. K. 1999 . Multiobjective optimization of an industrial nylon‐6 semibatch reactor system using genetic algorithm . Journal of Applied Polymer Science , 73 : 729 – 739 .
   Web of Science ®Google Scholar
• Bhaskar , V. , Gupta , S. K. and Ray , A. K. 2000 . Multiobjective optimization of an industrial wiped film poly(ethylene terephthalate) reactor . AIChE Journal , 46 : 1046 – 1058 .
   Web of Science ®Google Scholar
• Rajesh , J. K. , Gupta , S. K. , Rangaiah , G. P. and Ray , A. K. 2000 . Multiobjective optimization of steam reformer performance using genetic algorithm . Industrial and Engineering Chemistry Research , 39 : 706 – 717 .
   Web of Science ®Google Scholar
• Inamdar , S. V. , Gupta , S. K. and Saraf , D. N. 2004 . Multiobjective optimization of an industrial crude distillation unit using the elitist non‐dominated sorting genetic algorithm . Chemical Engineering Research and Design , 82 ( A5 ) : 611 – 623 .
   Web of Science ®Google Scholar
• Yuen , C. C. , Aatmeeyata , Gupta , S. K. and Ray , A. K. 2000 . Multiobjective optimization of membrane separation modules using genetic algorithm . Journal of Membrane Science , 176 : 177 – 196 .
   Web of Science ®Google Scholar
• Marriott , J. and Sorensen , Eva . 2003 . A general approach to modelling membrane modules . Chemical Engineering Science , 58 : 4975 – 4990 .
   Web of Science ®Google Scholar
• Marriott , J. and Sorensen , Eva . 2003 . The optimal design of membrane systems . Chemical Engineering Science , 58 : 4991 – 5004 .
   Web of Science ®Google Scholar
• Jain , S. and Gupta , S. K. 2004 . Analysis of modified surface pore flow model with concentration polarization and comparison with Spiegler‐Kedem model in reverse osmosis systems . Journal of Membrane Science , 232 : 45 – 61 .
   Web of Science ®Google Scholar
• Murthy , Z. V.P. 1996 . Studies on Reverse Osmosis Membrane Transport Models New Delhi, , India : Indian Institute of Technology . Chemical Engineering Department, Ph. D. Thesis
   Google Scholar
• Murthy , Z. V.P. and Gupta , S. K. 1997 . Estimation of mass transfer coefficient using a combined nonlinear membrane transport and film theory model . Desalination , 109 : 39 – 49 .
   Web of Science ®Google Scholar
• Murthy , Z. V.P. and Gupta , S. K. 1998 . Thinfilm composite polyamide membrane parameters estimation for the phenol‐water system by reverse osmosis . Separation Science and Technology , 33 : 2541 – 2557 .
   Web of Science ®Google Scholar
• Murthy , Z. V.P. and Gupta , S. K. 1999 . Sodium cyanide separation and parameters estimation for reverse osmosis thinfilm composite polyamide membrane . Journal of Membrane Science , 154 : 89 – 103 .
   Web of Science ®Google Scholar
• Vaidya , S. Y. , Simaria , A. V. and Murthy , Z. V.P. 2001 . Reverse osmosis transport models evaluation: A new approach . Indian Journal of Chemical Technology , 8 : 335 – 343 .
   Web of Science ®Google Scholar
• Murthy , Z. V.P. and Vora , M. M. 2004 . Prediction of reverse osmosis performance using artificial neural network . Indian Journal of Chemical Technology , 11 : 108 – 115 .
   Web of Science ®Google Scholar
• Soltanieh , M. and Gill , W. N. 1981 . Review of reverse osmosis membrane and transport models . Chemical Engineering Communications , 12 : 279 – 363 .
   Web of Science ®Google Scholar
• Murthy , Z. V.P. and Gupta , S. K. 1996 . Simple graphical method to estimate membrane transport parameters and mass transfer coefficient in a membrane cell . Separation Science and Technology , 31 : 77 – 94 .
   Web of Science ®Google Scholar
• Lamba , N. , Murthy , Z. V.P. and Kumar , R. 2002 . Membrane processing of an aqueous waste stream from catalyst manufacturing plant . Separation Science and Technology , 37 : 191 – 202 .
   Web of Science ®Google Scholar
• Koza , J. R. 1994 . Genetic programming as a means for programming computers by natural selection . Statistics and Computing (Historical Archive) , 4 : 87 – 112 .
   Web of Science ®Google Scholar
• Guria , C. , Bhattacharya , P. K. and Gupta , S. K. 2005 . Multi‐objective optimization of reverse osmosis desalination units using different adaptations of the non‐dominated sorting genetic algorithm (NSGA) . Computers and Chemical Engineering , 29 : 1977 – 1995 .
   Web of Science ®Google Scholar
• Ho , W. S.W. and Sirkar , K. K. 1992 . Membrane Handbook Edited by: Ho , W. S.W. New York : Van Nostrand Reinhold .
   Google Scholar
• Maskan , F. , Wiley , D. E. , Johnston , L. P.M. and Clements , D. J. 2000 . Optimal design of reverse osmosis module networks . AIChE Journal , 46 : 946 – 954 .
   Web of Science ®Google Scholar
• Wiley , D. E. , Fell , C. J.D. and Fane , A. G. 1985 . Optimization of membrane module design for brackish water desalination . Desalination , 52 : 249 – 265 .
   Web of Science ®Google Scholar
• Costa , C. B.B. and Filho , R. M. 2005 . Evaluation of optimisation techniques and control variable formulations for a batch cooling crystallization process . Chemical Engineering Science , 60 : 5312 – 5322 .
   Web of Science ®Google Scholar
• Babu , B. V. , Chakole , P. G. and Syed Mubeen , J. H. 2005 . Multiobjective differential evolution (MODE) for optimization of adiabatic styrene reactor . Chemical Engineering Science , 60 : 4822 – 4837 .
   Web of Science ®Google Scholar
• Mitra , K. and Gopinath , R. 2004 . Multiobjective optimization of an industrial grinding operation using elitist nondominated sorting genetic algorithm . Chemical Engineering Science , 59 : 385 – 396 .
   Web of Science ®Google Scholar
• Rajesh , J. K. , Gupta , S. K. , Rangaiah , G. P. and Ray , A. K. 2001 . Multi‐objective optimization of industrial hydrogen plants . Chemical Engineering Science , 56 : 999 – 1010 .
   Web of Science ®Google Scholar
• Tarafder , A. , Rangaiah , G. P. and Ray , A. K. 2005 . Multiobjective optimization of an industrial styrene monomer manufacturing process . Chemical Engineering Science , 60 : 347 – 363 .
   Web of Science ®Google Scholar
• Silva , C. M. and Biscaia , E. C. Jr. 2003 . Genetic algorithm development for multi‐objective optimization of batch free‐radical polymerization reactors . Computers and Chemical Engineering , 27 : 1329 – 1344 .
   Web of Science ®Google Scholar
• Tarafder , A. , Lee , B. C.S. , Ray , A. K. and Rangaiah , G. P. 2005 . Multiobjective optimization of an industrial ethylene reactor using a nondominated sorting genetic algorithm . Industrial and Engineering Chemistry Research , 44 : 124 – 141 .
   Web of Science ®Google Scholar
• Mitra , K. , Majumdar , S. and Raha , S. 2004 . Multiobjective optimization of a semibatch epoxy polymerization process using the elitist genetic algorithm . Industrial and Engineering Chemistry Research , 43 : 6055 – 6063 .
   Web of Science ®Google Scholar
• Bhaskar , V. , Ray , A. K. and Gupta , S. K. 2000 . Applications of multiobjective optimization in chemical engineering . Reviews in Chemical Engineering , 16 : 1 – 54 .
   Web of Science ®Google Scholar
• Deb , K. 2001 . Multi‐Objective Optimization Using Evolutionary Algorithms Chichester, , UK : Wiley .
   Google Scholar
• Coello Coello , C. A. , Van Veldhuizen , D. A. and Lamont , G. B. 2002 . Evolutionary Algorithms for Solving Multi‐Objective Problems New York : Kluwer .
   Google Scholar
• Goldberg , D. E. 1989 . Genetic Algorithms in Search, Optimisation, and Machine Learning Reading, MA : Addison‐Wesley .
   Google Scholar
• Guria , C. , Verma , M. , Mehrotra , S. P. and Gupta , S. K. 2005 . Multi‐objective optimal synthesis and design of froth flotation circuits for mineral processing using the jumping gene adaptation of genetic algorithm . Industrial and Engineering Chemistry Research , 44 : 2621 – 2633 .
   Web of Science ®Google Scholar
• Sarkar , D. and Modak , J. M. 2005 . Pareto‐optimal solutions for multi‐objective optimization of fed‐batch bioreactors using nondominated sorting genetic algorithm . Chemical Engineering Science , 60 : 481 – 492 .
   Web of Science ®Google Scholar
• Singh , M. K. , Banerjee , T. and Khanna , A. 2005 . Genetic algorithm to estimate interaction parameters of multicomponent systems for liquid‐liquid equilibria . Computers and Chemical Engineering , 29 : 1712 – 1719 .
   Web of Science ®Google Scholar
• Wongrat , W. , Srinophakun , T. and Srinophakun , P. 2005 . Modified genetic algorithm for nonlinear data reconciliation . Computers and Chemical Engineering , 29 : 1059 – 1067 .
   Web of Science ®Google Scholar
• Styczynski , M. P. and Stephanopoulos , G. 2005 . Overview of computational methods for the inference of gene regulatory networks . Computers and Chemical Engineering , 29 : 519 – 534 .
   Web of Science ®Google Scholar
• Katare , S. , Bhan , A. , Caruthers , J. M. , Delgass , W. N. and Venkatasubramanian , V. 2004 . A hybrid genetic algorithm for efficient parameter estimation of large kinetic models . Computers and Chemical Engineering , 28 : 2569 – 2581 .
   Web of Science ®Google Scholar
• Grosman , B. and Lewin , D. R. 2004 . Adaptive genetic programming for steady‐state process modeling . Computers and Chemical Engineering , 28 : 2779 – 2790 .
   Web of Science ®Google Scholar
• Ahmad , A. L. , Azid , I. A. , Yusof , A. R. and Seetharamu , K. N. 2004 . Emission control in palm oil mills using artificial neural network and genetic algorithm . Computers and Chemical Engineering , 28 : 2709 – 2715 .
   Web of Science ®Google Scholar
• Tarca , L. A. , Grandjean , B. P.A. and Larachi , F. 2004 . Embedding monotonicity and concavity in the training of neural networks by means of genetic algorithms: Application to multiphase flow . Computers and Chemical Engineering , 28 : 1701 – 1713 .
   Web of Science ®Google Scholar
• Leboreiro , J. and Acevedo , J. 2004 . Processes synthesis and design of distillation sequences using modular simulators: A genetic algorithm framework . Computers and Chemical Engineering , 28 : 1223 – 1236 .
   Web of Science ®Google Scholar
• Sarkar , D. and Modak , J. M. 2004 . Optimization of fed‐batch bioreactors using genetic algorithm: Multiple control variables . Computers and Chemical Engineering , 28 : 789 – 798 .
   Web of Science ®Google Scholar
• Elliott , L. , Ingham , D. B. , Kyne , A. G. , Mera , N. S. , Pourkashanian , M. and Wilson , C. W. 2005 . Reaction mechanism reduction and optimization using genetic algorithms . Industrial and Engineering Chemistry Research , 44 : 658 – 667 .
   Web of Science ®Google Scholar
• Balasubramanian , P. , Bettina , S. J. , Pushpavanam , S. and Balaraman , K. S. 2003 . Kinetic parameter estimation in hydrocracking using a combination of genetic algorithm and sequential quadratic programming . Industrial and Engineering Chemistry Research , 42 : 4723 – 4731 .
   Web of Science ®Google Scholar
• Suggala , S. V. and Bhattacharya , P. K. 2003 . Real coded genetic algorithm for optimization of pervaporation process parameters for removal of volatile organics from water . Industrial and Engineering Chemistry Research , 42 : 3118 – 3128 .
   Web of Science ®Google Scholar
• Elliott , L. , Ingham , D. B. , Kyne , A. G. , Mera , N. S. , Pourkashanian , M. and Wilson , C. W. 2003 . Multiobjective genetic algorithm optimization for calculating the reaction rate coefficients for hydrogen combustion . Industrial and Engineering Chemistry Research , 42 : 1215 – 1224 .
   Web of Science ®Google Scholar
• Sarkar , D. and Modak , J. M. 2003 . Optimisation of fed‐batch bioreactors using genetic algorithms . Chemical Engineering Science , 58 : 2283 – 2296 .
   Web of Science ®Google Scholar
• Lavric , V. , Iancu , P. and Plesu , V. 2005 . Genetic algorithm optimisation of water consumption and wastewater network topology . Journal of Cleaner Production , 13 : 1395 – 1405 .
   Web of Science ®Google Scholar
• Kasat , R. B. and Gupta , S. K. 2003 . Multi‐objective optimization of an industrial fluidized‐bed catalytic cracking unit (FCCU) using genetic algorithm (GA) with the jumping genes operator . Computers and Chemical Engineering , 27 : 1785 – 1800 .
   Web of Science ®Google Scholar
• Hinchliffe , M. P. and Willis , M. J. 2003 . Dynamic systems modelling using genetic programming . Computers and Chemical Engineering , 27 : 1841 – 1854 .
   Web of Science ®Google Scholar
• Alvarenga , G. B. and Mateus , G. R. 2004 . Hierarchical tournament selection genetic algorithm for the vehicle routing problem with time windows . Fourth International Conference on Hybrid Intelligent Systems (HIS'04) , : 410 – 415 .
   Google Scholar
• Emereev , A. V. 1999 . “ Modeling and Analysis of Genetic Algorithm with Tournament Selection ” . In Lecture Notes In Computer Science: Selected Papers from the 4th European Conference on Artificial Evolution Edited by: Fonlupt , C. , Hao , J‐K. , Lutton , E. , Ronald , E. M.A. and Schoenauer , M. Vol. 1829 , 84 – 94 . London : Springer‐Verlag .
   Google Scholar