Performance Comparison of Jumping Gene Adaptations of the Elitist Non‐dominated Sorting Genetic Algorithm

[1]  Santosh K. Gupta,et al.  Multiobjective optimization of the dynamic operation of an industrial steam reformer using the jumping gene adaptations of simulated annealing , 2006 .

[2]  Santosh K. Gupta,et al.  Multi-objective optimization of reverse osmosis desalination units using different adaptations of the non-dominated sorting genetic algorithm (NSGA) , 2005, Comput. Chem. Eng..

[3]  Aaditya Agarwal,et al.  Multiobjective Optimal Design of Heat Exchanger Networks Using New Adaptations of the Elitist Nondominated Sorting Genetic Algorithm, NSGA-II , 2008 .

[4]  Santosh K. Gupta,et al.  Multi-objective optimization of fuel oil blending using the jumping gene adaptation of genetic algorithm , 2007 .

[5]  Kishalay Mitra,et al.  Multiobjective dynamic optimization of an industrial Nylon 6 semibatch reactor using genetic algorit , 1998 .

[6]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[7]  G. R. Bhat,et al.  MO optimization of phthalic anhydride industrial catalytic reactors using guided GA with the adapted jumping gene operator , 2008 .

[8]  Lothar Thiele,et al.  Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study , 1998, PPSN.

[9]  G. P. Rangaiah,et al.  Multi-objective optimization of the operation of an industrial low-density polyethylene tubular reactor using genetic algorithm and its jumping gene adaptations , 2006 .

[10]  Manojkumar Ramteke,et al.  Biomimicking Altruistic Behavior of Honey Bees in Multi-objective Genetic Algorithm , 2009 .

[11]  Heike Trautmann,et al.  OCD: Online Convergence Detection for Evolutionary Multi-Objective Algorithms Based on Statistical Testing , 2009, EMO.

[12]  Santosh K. Gupta,et al.  Multi-objective optimization of an industrial fluidized-bed catalytic cracking unit (FCCU) using genetic algorithm (GA) with the jumping genes operator , 2003, Comput. Chem. Eng..

[13]  Gade Pandu Rangaiah,et al.  Multiobjective Optimization of an Industrial LPG Thermal Cracker using a First Principles Model , 2009 .

[14]  Silvia Curteanu,et al.  NSGA-II-RJG applied to multi-objective optimization of polymeric nanoparticles synthesis with silicone surfactants , 2011 .

[15]  Pranava Chaudhari,et al.  Multiobjective Optimization of a Fixed Bed Maleic Anhydride Reactor Using an Improved Biomimetic Adaptation of NSGA-II , 2012 .

[16]  Deoki N. Saraf,et al.  On-Line Optimizing Control of Bulk Free Radical Polymerization Reactors under Temporary Loss of Temperature Regulation: Experimental Study on a 1-L Batch Reactor , 2006 .

[17]  Chandan Guria,et al.  Multi-objective optimal synthesis and design of froth flotation circuits for mineral processing using the Jumping gene adaptation of genetic algorithm , 2005 .

[18]  Kim-Fung Man,et al.  A real-coding jumping gene genetic algorithm (RJGGA) for multiobjective optimization , 2007, Inf. Sci..

[19]  Ajay K. Ray,et al.  Design stage optimization of an industrial low-density polyethylene tubular reactor for multiple objectives using NSGA-II and its jumping gene adaptations , 2007 .

[20]  B. Sankararao,et al.  Multi-objective optimization of pressure swing adsorbers for air separation , 2007 .

[21]  Jing Liu,et al.  Multi-Objective Job Shop Scheduling Based on Multiagent Evolutionary Algorithm , 2010, SEAL.

[22]  Manojkumar Ramteke,et al.  Biomimetic Adaptation of the Evolutionary Algorithm, NSGA-II-aJG, Using the Biogenetic Law of Embryology for Intelligent Optimization , 2009 .

[23]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[24]  Santosh K. Gupta,et al.  Jumping gene adaptations of NSGA-II and their use in the multi-objective optimal design of shell and tube heat exchangers , 2008 .

[25]  Manojkumar Ramteke,et al.  Multiobjective Optimization of an Industrial Nylon-6 Semi Batch Reactor Using the a-Jumping Gene Adaptations of Genetic Algorithm and Simulated Annealing , 2008 .

[26]  Chandan Guria,et al.  Simultaneous optimization of the performance of flotation circuits and their simplification using the jumping gene adaptations of genetic algorithm-II: More complex problems , 2006 .

[27]  Kalyanmoy Deb,et al.  Improving convergence of evolutionary multi-objective optimization with local search: a concurrent-hybrid algorithm , 2011, Natural Computing.

[28]  Santosh K. Gupta,et al.  Modeling and simulation of fixed bed adsorbers (FBAs) for multi-component gaseous separations , 2007, Comput. Chem. Eng..