A novel fuzzy adaptive teaching–learning-based optimization (FATLBO) for solving structural optimization problems

This paper presents a new optimization algorithm called fuzzy adaptive teaching–learning-based optimization (FATLBO) for solving numerical structural problems. This new algorithm introduces three new mechanisms for increasing the searching capability of teaching–learning-based optimization namely status monitor, fuzzy adaptive teaching–learning strategies, and remedial operator. The performance of FATLBO is compared with well-known optimization methods on 26 unconstrained mathematical problems and five structural engineering design problems. Based on the obtained results, it can be concluded that FATLBO is able to deliver excellence and competitive performance in solving various structural optimization problems.

[1]  R. Venkata Rao,et al.  Multi-objective optimization of two stage thermoelectric cooler using a modified teaching-learning-based optimization algorithm , 2013, Eng. Appl. Artif. Intell..

[2]  Hae Chang Gea,et al.  STRUCTURAL OPTIMIZATION USING A NEW LOCAL APPROXIMATION METHOD , 1996 .

[3]  Yeh-Liang Hsu,et al.  Developing a fuzzy proportional–derivative controller optimization engine for engineering design optimization problems , 2007 .

[4]  尹 泳秀,et al.  Study on adaptive hybrid genetic algorithm and its applications to engineering design problems , 2005 .

[5]  A. Gandomi,et al.  Mixed variable structural optimization using Firefly Algorithm , 2011 .

[6]  R. Rao.  Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems , 2016 .

[7]  Min-Yuan Cheng,et al.  Hybrid Artificial Intelligence–Based PBA for Benchmark Functions and Facility Layout Design Optimization , 2012 .

[8]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[9]  Seyed Mohammad Mirjalili,et al.  Multi-Verse Optimizer: a nature-inspired algorithm for global optimization , 2015, Neural Computing and Applications.

[10]  Anima Naik,et al.  Data Clustering Based on Teaching-Learning-Based Optimization , 2011, SEMCCO.

[11]  K. Lee,et al.  A new structural optimization method based on the harmony search algorithm , 2004 .

[12]  S. O. Degertekin,et al.  Sizing truss structures using teaching-learning-based optimization , 2013 .

[13]  R. Venkata Rao,et al.  Teaching Learning Based Optimization Algorithm: And Its Engineering Applications , 2015 .

[14]  Taher Niknam,et al.  A new modified teaching-learning algorithm for reserve constrained dynamic economic dispatch , 2013, IEEE Transactions on Power Systems.

[15]  R. Venkata Rao,et al.  Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems , 2012, Inf. Sci..

[16]  Vedat Toğan,et al.  Design of planar steel frames using Teaching–Learning Based Optimization , 2012 .

[17]  Amir Hossein Gandomi,et al.  Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems , 2011, Engineering with Computers.

[18]  Tapabrata Ray,et al.  ENGINEERING DESIGN OPTIMIZATION USING A SWARM WITH AN INTELLIGENT INFORMATION SHARING AMONG INDIVIDUALS , 2001 .

[19]  Vivek Patel,et al.  Comparative performance of an elitist teaching-learning-based optimization algorithm for solving unconstrained optimization problems , 2013 .

[20]  H. Amir,et al.  Nonlinear Mixed-Discrete Structural Optimization , 1989 .

[21]  R. Rao,et al.  Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm , 2013 .

[22]  Vivek Patel,et al.  An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems , 2012 .

[23]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[24]  Taher Niknam,et al.  A new multi objective optimization approach based on TLBO for location of automatic voltage regulators in distribution systems , 2012, Eng. Appl. Artif. Intell..

[25]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[26]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[27]  R. Venkata Rao,et al.  Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems , 2016 .

[28]  Jung-Fa Tsai,et al.  Global optimization of nonlinear fractional programming problems in engineering design , 2005 .

[29]  C. J. Shih,et al.  Generalized Hopfield network based structural optimization using sequential unconstrained minimization technique with additional penalty strategy , 2002 .

[30]  Anima Naik,et al.  Improvement of Initial Cluster Center of C-means using Teaching Learning based Optimization☆ , 2012 .

[31]  Taher Niknam,et al.  Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants , 2012 .

[32]  R. Venkata Rao,et al.  Parameter optimization of modern machining processes using teaching-learning-based optimization algorithm , 2013, Eng. Appl. Artif. Intell..

[33]  G. G. Wang,et al.  Adaptive Response Surface Method Using Inherited Latin Hypercube Design Points , 2003 .

[34]  Singiresu S. Rao.  Engineering Optimization : Theory and Practice , 2010 .

[35]  R. Venkata Rao,et al.  Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..

[36]  K. Deb.  An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .

[37]  Min-Yuan Cheng,et al.  Symbiotic Organisms Search: A new metaheuristic optimization algorithm , 2014 .

[38]  R. Venkata Rao,et al.  Multi-objective optimization of combined Brayton and inverse Brayton cycles using advanced optimization algorithms , 2012 .

[39]  Judith S. Liebman,et al.  Discrete Structural Optimization , 1981 .

[40]  Min-Yuan Cheng,et al.  A novel Multiple Objective Symbiotic Organisms Search (MOSOS) for time-cost-labor utilization tradeoff problem , 2016, Knowl. Based Syst..