A novel bat algorithm with double mutation operators and its application to low-velocity impact localization problem

Abstract The low-velocity impact localization in the plate structure of the ship is a critical problem which can be considered as a nonlinear optimization problem. The bat algorithm (BA) has been widely used to solve nonlinear optimization problems. However, the standard BA exhibits poor performance on complex problems because of its premature convergence. In this study, a novel bat algorithm with double mutation operators (TMBA), in which a modified time factor and two mutation operators are integrated, is proposed to enhance BA’s performance on nonlinear optimization problems. Classical benchmark functions are employed to analyze the contributions of the three modifications and demonstrate the significant improvement of TMBA. For the low-velocity impact localization problem, the low-velocity impact localization system based on fiber Bragg grating (FBG) sensors is utilized to receive the impact signals. The wavelet threshold de-noising method and the generalized cross-correlation method are both applied to the extraction of time differences between the impact signals. Then, the proposed algorithm and several well-known optimization algorithms are adopted to solve the minimization fitness function which is established using the triangulation method. The statistical results indicate that TMBA is more feasible and effective for solving the low-velocity impact localization problem.

[1]  Ming Wang,et al.  Acoustic Emission Source Localization System Using Fiber Bragg Grating Sensors and a Barycentric Coordinate-Based Algorithm , 2018, J. Sensors.

[2]  P. N. Suganthan,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[3]  A. Tobias,et al.  Acoustic-emission source location in two dimensions by an array of three sensors , 1976 .

[4]  Aman Jantan,et al.  Hybridizing Bat Algorithm with Modified Pitch Adjustment Operator for Numerical Optimization Problems , 2017 .

[5]  Ali Rıza Yıldız,et al.  Moth-flame optimization algorithm to determine optimal machining parameters in manufacturing processes , 2017 .

[6]  Ali Rıza Yıldız,et al.  The Harris hawks optimization algorithm, salp swarm algorithm, grasshopper optimization algorithm and dragonfly algorithm for structural design optimization of vehicle components , 2019, Materials Testing.

[7]  Francesco Ciampa,et al.  A new algorithm for acoustic emission localization and flexural group velocity determination in anisotropic structures , 2010 .

[8]  Junzo Watada,et al.  Gaussian-PSO with fuzzy reasoning based on structural learning for training a Neural Network , 2016, Neurocomputing.

[9]  Dae-Un Sung,et al.  Impact Monitoring of Smart Composite Laminates Using Neural Network and Wavelet Analysis , 2000 .

[10]  Qi Wu,et al.  Acoustic emission detection and position identification of transverse cracks in carbon fiber–reinforced plastic laminates by using a novel optical fiber ultrasonic sensing system , 2015 .

[11]  Lisheng Liu,et al.  Localization of impact on composite plates based on integrated wavelet transform and hybrid minimization algorithm , 2017 .

[12]  Qi Liu,et al.  A novel hybrid bat algorithm for solving continuous optimization problems , 2018, Appl. Soft Comput..

[13]  Amir Hossein Gandomi,et al.  Chaotic bat algorithm , 2014, J. Comput. Sci..

[14]  Lei Jia,et al.  Low Velocity Impact Localization on CFRP Based on FBG Sensors and ELM Algorithm , 2015, IEEE Sensors Journal.

[15]  A. Kaveh,et al.  A novel heuristic optimization method: charged system search , 2010 .

[16]  Nantiwat Pholdee,et al.  Hybrid real-code population-based incremental learning and differential evolution for many-objective optimisation of an automotive floor-frame , 2017, International Journal of Vehicle Design.

[17]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[18]  Quan-Ke Pan,et al.  A local-best harmony search algorithm with dynamic subpopulations , 2010 .

[19]  Wei Chen,et al.  A Hybrid Multiobjective Bat Algorithm for Fuzzy Portfolio Optimization with Real-World Constraints , 2018, International Journal of Fuzzy Systems.

[20]  Jinjun Chen,et al.  Optimal LEACH protocol with modified bat algorithm for big data sensing systems in Internet of Things , 2019, J. Parallel Distributed Comput..

[21]  S. Arunachalam,et al.  Hybridizing bat algorithm with artificial bee colony for combined heat and power economic dispatch , 2018, Appl. Soft Comput..

[22]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[23]  Rob Law,et al.  Cauchy mutation based on objective variable of Gaussian particle swarm optimization for parameters selection of SVM , 2011, Expert Syst. Appl..

[24]  Xiao-Zhi Gao,et al.  A Novel Hybrid Bat Algorithm with Differential Evolution Strategy for Constrained Optimization , 2015 .

[25]  Hossam Faris,et al.  An efficient binary Salp Swarm Algorithm with crossover scheme for feature selection problems , 2018, Knowl. Based Syst..

[26]  Mesut Gündüz,et al.  Artificial bee colony algorithm with variable search strategy for continuous optimization , 2015, Inf. Sci..

[27]  Francesco Ciampa,et al.  Impact detection in anisotropic materials using a time reversal approach , 2012 .

[28]  Hamed Shah-Hosseini,et al.  Principal components analysis by the galaxy-based search algorithm: a novel metaheuristic for continuous optimisation , 2011, Int. J. Comput. Sci. Eng..

[29]  Mohammed Azmi Al-Betar,et al.  Island bat algorithm for optimization , 2018, Expert systems with applications.

[30]  Oguz Altun,et al.  A novel meta-heuristic algorithm: Dynamic Virtual Bats Algorithm , 2016, Inf. Sci..

[31]  Aijia Ouyang,et al.  Powell-Based Bat Algorithm for Solving Nonlinear Equations , 2018, ICIC.

[32]  Pratik Shrestha,et al.  Impact localization on composite structure using FBG sensors and novel impact localization technique based on error outliers , 2016 .

[33]  Lin Chen,et al.  Acoustic Source Localization Based on Generalized Cross-correlation Time-delay Estimation , 2011 .

[34]  Hossam Faris,et al.  Harris hawks optimization: Algorithm and applications , 2019, Future Gener. Comput. Syst..

[35]  Jinjun Chen,et al.  A Novel Bat Algorithm with Multiple Strategies Coupling for Numerical Optimization , 2019, Mathematics.

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

[37]  B. Suman,et al.  A survey of simulated annealing as a tool for single and multiobjective optimization , 2006, J. Oper. Res. Soc..

[38]  Andrew Lewis,et al.  Grasshopper Optimisation Algorithm: Theory and application , 2017, Adv. Eng. Softw..

[39]  Pingping Chen,et al.  Simplex Bat Algorithm for Solving System of Non-linear Equations , 2017, ICIC.

[40]  Carol Ann Featherston,et al.  Determination of Damage Levels of Composite Plates after Low Velocity Impacts Using Acoustic Emission , 2006 .

[41]  Selim Yilmaz,et al.  A new modification approach on bat algorithm for solving optimization problems , 2015, Appl. Soft Comput..

[42]  Keith Worden,et al.  Impact Location and Quantification on a Composite Panel using Neural Networks and a Genetic Algorithm , 2000 .

[43]  Nantiwat Pholdee,et al.  A new hybrid Harris hawks-Nelder-Mead optimization algorithm for solving design and manufacturing problems , 2019, Materials Testing.

[44]  Xiao Zhi Gao,et al.  An adaptive reinforcement learning-based bat algorithm for structural design problems , 2018 .

[45]  Ali Rıza Yıldız,et al.  Optimization of thin-wall structures using hybrid gravitational search and Nelder-Mead algorithm , 2015 .

[46]  Xin Chen,et al.  A new bat algorithm based on iterative local search and stochastic inertia weight , 2018, Expert Syst. Appl..

[47]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[48]  Jeng-Shyang Pan,et al.  Hybrid Bat Algorithm with Artificial Bee Colony , 2014, ECC.

[49]  Betül Sultan Yıldız,et al.  Natural frequency optimization of vehicle components using the interior search algorithm , 2017 .

[50]  Maria Augusta Neto,et al.  Low velocity impact damage evaluation in fiber glass composite plates using PZT sensors , 2013 .

[51]  Tribikram Kundu,et al.  Acoustic source localization. , 2014, Ultrasonics.

[52]  Giangiacomo Minak,et al.  Damage evaluation of laminated composites under low-velocity impact tests using acoustic emission method , 2017 .

[53]  Betül Sultan Yıldız,et al.  Fatigue-based structural optimisation of vehicle components , 2017 .

[54]  Fred W. Glover,et al.  Tabu search—Uncharted domains , 2007, Ann. Oper. Res..

[55]  Zong Woo Geem,et al.  A survey on applications of the harmony search algorithm , 2013, Eng. Appl. Artif. Intell..

[56]  Sadiq M. Sait,et al.  The Harris hawks, grasshopper and multi-verse optimization algorithms for the selection of optimal machining parameters in manufacturing operations , 2019, Materials Testing.

[57]  Lei Wu,et al.  A new improved fruit fly optimization algorithm IAFOA and its application to solve engineering optimization problems , 2017, Knowl. Based Syst..

[58]  Ali Rıza Yıldız,et al.  Comparison of grey wolf, whale, water cycle, ant lion and sine-cosine algorithms for the optimization of a vehicle engine connecting rod , 2018 .

[59]  Aijia Ouyang,et al.  Steepest Descent Bat Algorithm for Solving Systems of Non-linear Equations , 2018, ICIC.

[60]  Ibrahim Eksin,et al.  A new optimization method: Big Bang-Big Crunch , 2006, Adv. Eng. Softw..

[61]  Hammoudi Abderazek,et al.  A Comparative Study of Recent Non-traditional Methods for Mechanical Design Optimization , 2019, Archives of Computational Methods in Engineering.

[62]  Lei Jia,et al.  Low velocity impact localization system of CFRP using fiber Bragg grating sensors , 2015 .

[63]  Concepción A. Monje,et al.  Fractional-order PID control of a MIMO distillation column process using improved bat algorithm , 2018, Soft Comput..

[64]  Hwa Jen Yap,et al.  Cuckoo search algorithm based design of interval Type-2 Fuzzy PID Controller for Furuta pendulum system , 2017, Eng. Appl. Artif. Intell..

[65]  Anand Jayant Kulkarni,et al.  Socio evolution & learning optimization algorithm: A socio-inspired optimization methodology , 2018, Future Gener. Comput. Syst..

[66]  Chun-Gon Kim,et al.  Impact localization on a composite stiffened panel using reference signals with efficient training process , 2016 .

[67]  Oscar Castillo,et al.  A New Bat Algorithm Augmentation Using Fuzzy Logic for Dynamical Parameter Adaptation , 2015, MICAI.

[68]  Cláudio R. M. Silva,et al.  Modified bat algorithm with cauchy mutation and elite opposition-based learning , 2017, 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI).

[69]  Jian Xie,et al.  A Novel Bat Algorithm Based on Differential Operator and Lévy Flights Trajectory , 2013, Comput. Intell. Neurosci..

[70]  Jin-Hyuk Kim,et al.  Real‐time impact identification algorithm for composite structures using fiber Bragg grating sensors , 2012 .

[71]  Jun Li,et al.  Grey wolf optimization evolving kernel extreme learning machine: Application to bankruptcy prediction , 2017, Eng. Appl. Artif. Intell..

[72]  Ali R. Yildiz,et al.  Structural design of vehicle components using gravitational search and charged system search algorithms , 2015 .

[73]  Xin-She Yang,et al.  New directional bat algorithm for continuous optimization problems , 2017, Expert Syst. Appl..

[74]  Hareesh V. Tippur,et al.  A method for measuring mode I crack tip constraint under static and dynamic loading conditions , 2004 .

[75]  Ali Rıza Yıldız,et al.  Optimum design of cam-roller follower mechanism using a new evolutionary algorithm , 2018 .

[76]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[77]  Fuh-Gwo Yuan,et al.  Impact source identification in finite isotropic plates using a time-reversal method: theoretical study , 2010 .

[78]  Y. J. Cao,et al.  Evolutionary programming , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[79]  Yu Liu,et al.  A novel bat algorithm with habitat selection and Doppler effect in echoes for optimization , 2015, Expert Syst. Appl..

[80]  Yungang Liu,et al.  A Hybrid Bat Algorithm for Economic Dispatch With Random Wind Power , 2018, IEEE Transactions on Power Systems.

[81]  Flávio Neves,et al.  A micro-genetic algorithm for multi-objective scheduling of a real world pipeline network , 2013, Eng. Appl. Artif. Intell..

[82]  Gaige Wang,et al.  A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization , 2013, J. Appl. Math..

[83]  Liang Gao,et al.  An improved fruit fly optimization algorithm for continuous function optimization problems , 2014, Knowl. Based Syst..

[84]  Seyed Mohammad Mirjalili,et al.  Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm , 2015, Knowl. Based Syst..

[85]  Wen-Tsao Pan,et al.  A new Fruit Fly Optimization Algorithm: Taking the financial distress model as an example , 2012, Knowl. Based Syst..

[86]  Morteza Kiani,et al.  A Comparative Study of Non-traditional Methods for Vehicle Crashworthiness and NVH Optimization , 2016 .

[87]  Wan Yusoff Wan Azhar,et al.  Optimization of the PID-PD parameters of the overhead crane control system by using PSO algorithm , 2019 .

[88]  Hassan Rashidi,et al.  An enhanced genetic algorithm with new operators for task scheduling in heterogeneous computing systems , 2017, Eng. Appl. Artif. Intell..

[89]  Saeed Farzin,et al.  Hybrid Bat & Particle Swarm Algorithm for optimization of labyrinth spillway based on half & quarter round crest shapes , 2019, Flow Measurement and Instrumentation.