
Previous Article
A hydrothermal problem with nonsmooth Lagrangian
 JIMO Home
 This Issue

Next Article
Optimal stochastic investment games under Markov regime switching market
Solving structural engineering design optimization problems using an artificial bee colony algorithm
1.  School of Mathematics and Computer Applications, Thapar University Patiala, Patiala  147004, Punjab, India 
References:
[1] 
B. Akay and D. Karaboga, Artificial bee colony algorithm for largescale problems and engineering design optimization,, Journal of Intelligent Manufacturing, 23 (2012), 1001. doi: 10.1007/s1084501003934. 
[2] 
J. S. Arora, Introduction to Optimum Design,, McGrawHill, (1989). 
[3] 
A. D. Belegundu, A Study of Mathematical Programming Methods for Structural Optimization,, PhD thesis, (1982). 
[4] 
L. C. Cagnina, S. C. Esquivel and C. A. C. Coello, Solving engineering optimization problems with the simple constrained particle swarm optimizer,, Informatica, 32 (2008), 319. 
[5] 
L. S. Coelho, Gaussian quantumbehaved particle swarm optimization approaches for constrained engineering design problems,, Expert Systems with Applications, 37 (2010), 1676. doi: 10.1016/j.eswa.2009.06.044. 
[6] 
C. A. C. Coello, Treating constraints as objectives for singleobjective evolutionary optimization,, Engineering Optimization, 32 (2000), 275. doi: 10.1080/03052150008941301. 
[7] 
C. A. C. Coello, Use of a self adaptive penalty approach for engineering optimization problems,, Computers in Industry, 41 (2000), 113. doi: 10.1016/S01663615(99)000469. 
[8] 
C. A. C. Coello and E. M. Montes, Constraint handling in genetic algorithms through the use of dominancebased tournament selection,, Advanced Engineering Informatics, 16 (2002), 193. doi: 10.1016/S14740346(02)000113. 
[9] 
K. Deb, Optimal design of a welded beam via genetic algorithms,, AIAA Journal, 29 (1991), 2013. 
[10] 
K. Deb, An efficient constraint handling method for genetic algorithms,, Computer Methods in Applied Mechanics and Engineering, 186 (2000), 311. doi: 10.1016/S00457825(99)003898. 
[11] 
K. Deb and A. S. Gene, A robust optimal design technique for mechanical component design,, (Eds. D. Dasgupta, (1997), 497. doi: 10.1007/9783662034231_27. 
[12] 
K. Deb and M. Goyal, A combined genetic adaptive search (GeneAS) for engineering design,, Computer Science and Informatics, 26 (1986), 30. 
[13] 
G. G. Dimopoulos, Mixedvariable engineering optimization based on evolutionary and social metaphors,, Computer Methods in Applied Mechanics and Engineering, 196 (2007), 803. doi: 10.1016/j.cma.2006.06.010. 
[14] 
M. Fesanghary, M. Mahdavi, M. MinaryJolandan and Y. Alizadeh, Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems,, Computer Methods in Applied Mechanics and Engineering, 197 (2008), 3080. doi: 10.1016/j.cma.2008.02.006. 
[15] 
A. H. Gandomi, X. S. Yang, and A. H. Alavi, Mixed variable structural optimization using firefly algorithm,, Computers & Structures, 89 (): 2325. 
[16] 
A. H. Gandomi, X. S. Yang and A. Alavi, Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems,, Engineering with Computers, 29 (2003), 17. doi: 10.1007/s003660110241y. 
[17] 
Q. He and L. Wang, An effective co  evolutionary particle swarm optimization for constrained engineering design problems,, Engineering Applications of Artificial Intelligence, 20 (2007), 89. doi: 10.1016/j.engappai.2006.03.003. 
[18] 
S. He, E. Prempain and Q. H. Wu, An improved particle swarm optimizer for mechanical design optimization problems,, Engineering Optimization, 36 (2004), 585. doi: 10.1080/03052150410001704854. 
[19] 
A. R. Hedar and M. Fukushima, Derivative  free filter simulated annealing method for constrained continuous global optimization,, Journal of Global Optimization, 35 (2006), 521. doi: 10.1007/s108980053693z. 
[20] 
D. M. Himmelblau, Applied Nonlinear Programming,, McGrawHill, (1972). 
[21] 
A. Homaifar, S. H. Y. Lai and X. Qi, Constrained optimization via genetic algorithms,, Simulation, 62 (1994), 242. doi: 10.1177/003754979406200405. 
[22] 
Y. L. Hsu and T. C. Liu, Developing a fuzzy proportional derivative controller optimization engine for engineering design optimization problems,, Engineering Optimization, 39 (2007), 679. doi: 10.1080/03052150701252664. 
[23] 
X. H. Hu, R. C. Eberhart and Y. H. Shi, Engineering optimization with particle swarm,, Proceedings of the 2003 IEEE Swarm Intelligence Symposium, (2003), 53. 
[24] 
S. F. Hwang and R. S. He, A hybrid realparameter genetic algorithm for function optimization,, Advanced Engineering Informatics, 20 (2006), 7. doi: 10.1016/j.aei.2005.09.001. 
[25] 
B. K. Kannan and S. N. Kramer, An augmented lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical design,, Transactions of the ASME, 116 (1994), 405. doi: 10.1115/1.2919393. 
[26] 
D. Karaboga, An Idea Based on Honey Bee Swarm for Numerical Optimization,, Technical report, (2005). 
[27] 
D. Karaboga and B. Akay, A comparative study of artificial bee colony algorithm,, Applied Mathematics and Computation, 214 (2009), 108. doi: 10.1016/j.amc.2009.03.090. 
[28] 
D. Karaboga, B. Gorkemli, C. Ozturk and N. Karaboga, A comprehensive survey: Artificial bee colony (abc) algorithm and applications,, Artificial Intelligence Review, (2012), 1. doi: 10.1007/s1046201293280. 
[29] 
D. Karaboga and C. Ozturk, A novel clustering approach: Artificial bee colony (ABC) algorithm,, Applied Soft Computing, 11 (2011), 652. doi: 10.1016/j.asoc.2009.12.025. 
[30] 
A. Kaveh and S. Talatahari, Engineering optimization with hybrid particle swarm and ant colony optimization,, Asian journal of civil engineering (building and housing), 10 (2009), 611. 
[31] 
A. Kaveh and S. Talatahari, An improved ant colony optimization for constrained engineering design problems,, Engineering Computations, 27 (2010), 155. doi: 10.1108/02644401011008577. 
[32] 
K. S. Lee and Z. W. Geem, A new metaheuristic algorithm for continuous engineering optimization: harmony search theory and practice,, Computer Methods in Applied Mechanics and Engineering, 194 (2005), 3902. doi: 10.1016/j.cma.2004.09.007. 
[33] 
M. Mahdavi, M. Fesanghary and E. Damangir, An improved harmony search algorithm for solving optimization problems,, Applied Mathematics and Computation, 188 (2007), 1567. doi: 10.1016/j.amc.2006.11.033. 
[34] 
V. K. Mehta and B. Dasgupta, A constrained optimization algorithm based on the simplex search method,, Engineering Optimization, 44 (2012), 537. doi: 10.1080/0305215X.2011.598520. 
[35] 
Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs,, Springer  Verlag, (1994). 
[36] 
E. M. Montes and C. A. C. Coello, An empirical study about the usefulness of evolution strategies to solve constrained optimization problems,, International Journal of General Systems, 37 (2008), 443. doi: 10.1080/03081070701303470. 
[37] 
E. M. Montes, C. A. C. Coello, J. V. Reyes and L. M. Davila, Multiple trial vectors in differential evolution for engineering design,, Engineering Optimization, 39 (2007), 567. doi: 10.1080/03052150701364022. 
[38] 
M. G. H. Omran and A. Salman, Constrained optimization using CODEQ,, Chaos, 42 (2009), 662. 
[39] 
K. M. Ragsdell and D. T. Phillips, Optimal design of a class of welded structures using geometric programming,, ASME Journal of Engineering for Industries, 98 (1976), 1021. doi: 10.1115/1.3438995. 
[40] 
K. H. Raj, R. S. Sharma, G. S. Mishra, A. Dua and C. Patvardhan, An evolutionary computational technique for constrained optimisation in engineering design,, Journal of the Institution of Engineers India Part Me Mechanical Engineering Division, 86 (2005), 121. 
[41] 
S. S. Rao, Engineering Optimization: Theory and Practice,, 3rd edition, (1996). 
[42] 
T. Ray and K. M. Liew, Society and civilization : An optimization algorithm based on the simulation of social behavior,, IEEE Transactions on Evolutionary Computation, 7 (2003), 386. doi: 10.1109/TEVC.2003.814902. 
[43] 
T. Ray and P. Saini, Engineering design optimization using a swarm with an intelligent information sharing among individuals,, Engineering Optimization, 33 (2001), 735. doi: 10.1080/03052150108940941. 
[44] 
E. Sandgren, Nonlinear integer and discrete programming in mechanical design,, Proceedings of the ASME Design Technology Conference, (1988), 95. 
[45] 
Y. Shi and R. C. Eberhart, A modified particle swarm optimizer,, IEEE International Conference on Evolutionary Computation, (1998), 69. 
[46] 
J. Tsai, Global optimization of nonlinear fractional programming problems in engineering design,, Engineering Optimization, 37 (2005), 399. doi: 10.1080/03052150500066737. 
[47] 
C. Zhang and H. P. Wang, Mixeddiscrete nonlinear optimization with simulated annealing,, Engineering Optimization, 21 (1993), 277. doi: 10.1080/03052159308940980. 
[48] 
M. Zhang, W. Luo and X. Wang, Differential evolution with dynamic stochastic selection for constrained optimization,, Information Sciences, 178 (2008), 3043. doi: 10.1016/j.ins.2008.02.014. 
show all references
References:
[1] 
B. Akay and D. Karaboga, Artificial bee colony algorithm for largescale problems and engineering design optimization,, Journal of Intelligent Manufacturing, 23 (2012), 1001. doi: 10.1007/s1084501003934. 
[2] 
J. S. Arora, Introduction to Optimum Design,, McGrawHill, (1989). 
[3] 
A. D. Belegundu, A Study of Mathematical Programming Methods for Structural Optimization,, PhD thesis, (1982). 
[4] 
L. C. Cagnina, S. C. Esquivel and C. A. C. Coello, Solving engineering optimization problems with the simple constrained particle swarm optimizer,, Informatica, 32 (2008), 319. 
[5] 
L. S. Coelho, Gaussian quantumbehaved particle swarm optimization approaches for constrained engineering design problems,, Expert Systems with Applications, 37 (2010), 1676. doi: 10.1016/j.eswa.2009.06.044. 
[6] 
C. A. C. Coello, Treating constraints as objectives for singleobjective evolutionary optimization,, Engineering Optimization, 32 (2000), 275. doi: 10.1080/03052150008941301. 
[7] 
C. A. C. Coello, Use of a self adaptive penalty approach for engineering optimization problems,, Computers in Industry, 41 (2000), 113. doi: 10.1016/S01663615(99)000469. 
[8] 
C. A. C. Coello and E. M. Montes, Constraint handling in genetic algorithms through the use of dominancebased tournament selection,, Advanced Engineering Informatics, 16 (2002), 193. doi: 10.1016/S14740346(02)000113. 
[9] 
K. Deb, Optimal design of a welded beam via genetic algorithms,, AIAA Journal, 29 (1991), 2013. 
[10] 
K. Deb, An efficient constraint handling method for genetic algorithms,, Computer Methods in Applied Mechanics and Engineering, 186 (2000), 311. doi: 10.1016/S00457825(99)003898. 
[11] 
K. Deb and A. S. Gene, A robust optimal design technique for mechanical component design,, (Eds. D. Dasgupta, (1997), 497. doi: 10.1007/9783662034231_27. 
[12] 
K. Deb and M. Goyal, A combined genetic adaptive search (GeneAS) for engineering design,, Computer Science and Informatics, 26 (1986), 30. 
[13] 
G. G. Dimopoulos, Mixedvariable engineering optimization based on evolutionary and social metaphors,, Computer Methods in Applied Mechanics and Engineering, 196 (2007), 803. doi: 10.1016/j.cma.2006.06.010. 
[14] 
M. Fesanghary, M. Mahdavi, M. MinaryJolandan and Y. Alizadeh, Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems,, Computer Methods in Applied Mechanics and Engineering, 197 (2008), 3080. doi: 10.1016/j.cma.2008.02.006. 
[15] 
A. H. Gandomi, X. S. Yang, and A. H. Alavi, Mixed variable structural optimization using firefly algorithm,, Computers & Structures, 89 (): 2325. 
[16] 
A. H. Gandomi, X. S. Yang and A. Alavi, Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems,, Engineering with Computers, 29 (2003), 17. doi: 10.1007/s003660110241y. 
[17] 
Q. He and L. Wang, An effective co  evolutionary particle swarm optimization for constrained engineering design problems,, Engineering Applications of Artificial Intelligence, 20 (2007), 89. doi: 10.1016/j.engappai.2006.03.003. 
[18] 
S. He, E. Prempain and Q. H. Wu, An improved particle swarm optimizer for mechanical design optimization problems,, Engineering Optimization, 36 (2004), 585. doi: 10.1080/03052150410001704854. 
[19] 
A. R. Hedar and M. Fukushima, Derivative  free filter simulated annealing method for constrained continuous global optimization,, Journal of Global Optimization, 35 (2006), 521. doi: 10.1007/s108980053693z. 
[20] 
D. M. Himmelblau, Applied Nonlinear Programming,, McGrawHill, (1972). 
[21] 
A. Homaifar, S. H. Y. Lai and X. Qi, Constrained optimization via genetic algorithms,, Simulation, 62 (1994), 242. doi: 10.1177/003754979406200405. 
[22] 
Y. L. Hsu and T. C. Liu, Developing a fuzzy proportional derivative controller optimization engine for engineering design optimization problems,, Engineering Optimization, 39 (2007), 679. doi: 10.1080/03052150701252664. 
[23] 
X. H. Hu, R. C. Eberhart and Y. H. Shi, Engineering optimization with particle swarm,, Proceedings of the 2003 IEEE Swarm Intelligence Symposium, (2003), 53. 
[24] 
S. F. Hwang and R. S. He, A hybrid realparameter genetic algorithm for function optimization,, Advanced Engineering Informatics, 20 (2006), 7. doi: 10.1016/j.aei.2005.09.001. 
[25] 
B. K. Kannan and S. N. Kramer, An augmented lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical design,, Transactions of the ASME, 116 (1994), 405. doi: 10.1115/1.2919393. 
[26] 
D. Karaboga, An Idea Based on Honey Bee Swarm for Numerical Optimization,, Technical report, (2005). 
[27] 
D. Karaboga and B. Akay, A comparative study of artificial bee colony algorithm,, Applied Mathematics and Computation, 214 (2009), 108. doi: 10.1016/j.amc.2009.03.090. 
[28] 
D. Karaboga, B. Gorkemli, C. Ozturk and N. Karaboga, A comprehensive survey: Artificial bee colony (abc) algorithm and applications,, Artificial Intelligence Review, (2012), 1. doi: 10.1007/s1046201293280. 
[29] 
D. Karaboga and C. Ozturk, A novel clustering approach: Artificial bee colony (ABC) algorithm,, Applied Soft Computing, 11 (2011), 652. doi: 10.1016/j.asoc.2009.12.025. 
[30] 
A. Kaveh and S. Talatahari, Engineering optimization with hybrid particle swarm and ant colony optimization,, Asian journal of civil engineering (building and housing), 10 (2009), 611. 
[31] 
A. Kaveh and S. Talatahari, An improved ant colony optimization for constrained engineering design problems,, Engineering Computations, 27 (2010), 155. doi: 10.1108/02644401011008577. 
[32] 
K. S. Lee and Z. W. Geem, A new metaheuristic algorithm for continuous engineering optimization: harmony search theory and practice,, Computer Methods in Applied Mechanics and Engineering, 194 (2005), 3902. doi: 10.1016/j.cma.2004.09.007. 
[33] 
M. Mahdavi, M. Fesanghary and E. Damangir, An improved harmony search algorithm for solving optimization problems,, Applied Mathematics and Computation, 188 (2007), 1567. doi: 10.1016/j.amc.2006.11.033. 
[34] 
V. K. Mehta and B. Dasgupta, A constrained optimization algorithm based on the simplex search method,, Engineering Optimization, 44 (2012), 537. doi: 10.1080/0305215X.2011.598520. 
[35] 
Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs,, Springer  Verlag, (1994). 
[36] 
E. M. Montes and C. A. C. Coello, An empirical study about the usefulness of evolution strategies to solve constrained optimization problems,, International Journal of General Systems, 37 (2008), 443. doi: 10.1080/03081070701303470. 
[37] 
E. M. Montes, C. A. C. Coello, J. V. Reyes and L. M. Davila, Multiple trial vectors in differential evolution for engineering design,, Engineering Optimization, 39 (2007), 567. doi: 10.1080/03052150701364022. 
[38] 
M. G. H. Omran and A. Salman, Constrained optimization using CODEQ,, Chaos, 42 (2009), 662. 
[39] 
K. M. Ragsdell and D. T. Phillips, Optimal design of a class of welded structures using geometric programming,, ASME Journal of Engineering for Industries, 98 (1976), 1021. doi: 10.1115/1.3438995. 
[40] 
K. H. Raj, R. S. Sharma, G. S. Mishra, A. Dua and C. Patvardhan, An evolutionary computational technique for constrained optimisation in engineering design,, Journal of the Institution of Engineers India Part Me Mechanical Engineering Division, 86 (2005), 121. 
[41] 
S. S. Rao, Engineering Optimization: Theory and Practice,, 3rd edition, (1996). 
[42] 
T. Ray and K. M. Liew, Society and civilization : An optimization algorithm based on the simulation of social behavior,, IEEE Transactions on Evolutionary Computation, 7 (2003), 386. doi: 10.1109/TEVC.2003.814902. 
[43] 
T. Ray and P. Saini, Engineering design optimization using a swarm with an intelligent information sharing among individuals,, Engineering Optimization, 33 (2001), 735. doi: 10.1080/03052150108940941. 
[44] 
E. Sandgren, Nonlinear integer and discrete programming in mechanical design,, Proceedings of the ASME Design Technology Conference, (1988), 95. 
[45] 
Y. Shi and R. C. Eberhart, A modified particle swarm optimizer,, IEEE International Conference on Evolutionary Computation, (1998), 69. 
[46] 
J. Tsai, Global optimization of nonlinear fractional programming problems in engineering design,, Engineering Optimization, 37 (2005), 399. doi: 10.1080/03052150500066737. 
[47] 
C. Zhang and H. P. Wang, Mixeddiscrete nonlinear optimization with simulated annealing,, Engineering Optimization, 21 (1993), 277. doi: 10.1080/03052159308940980. 
[48] 
M. Zhang, W. Luo and X. Wang, Differential evolution with dynamic stochastic selection for constrained optimization,, Information Sciences, 178 (2008), 3043. doi: 10.1016/j.ins.2008.02.014. 
[1] 
Guangzhou Chen, Guijian Liu, Jiaquan Wang, Ruzhong Li. Identification of water quality model parameters using artificial bee colony algorithm. Numerical Algebra, Control & Optimization, 2012, 2 (1) : 157165. doi: 10.3934/naco.2012.2.157 
[2] 
Roya Soltani, Seyed Jafar Sadjadi, Mona Rahnama. Artificial intelligence combined with nonlinear optimization techniques and their application for yield curve optimization. Journal of Industrial & Management Optimization, 2017, 13 (4) : 17011721. doi: 10.3934/jimo.2017014 
[3] 
A. Zeblah, Y. Massim, S. Hadjeri, A. Benaissa, H. Hamdaoui. Optimization for seriesparallel continuous power systems with buffers under reliability constraints using ant colony. Journal of Industrial & Management Optimization, 2006, 2 (4) : 467479. doi: 10.3934/jimo.2006.2.467 
[4] 
Hassen Aydi, Ayman Kachmar. Magnetic vortices for a GinzburgLandau type energy with discontinuous constraint. II. Communications on Pure & Applied Analysis, 2009, 8 (3) : 977998. doi: 10.3934/cpaa.2009.8.977 
[5] 
Ziteng Wang, ShuCherng Fang, Wenxun Xing. On constraint qualifications: Motivation, design and interrelations. Journal of Industrial & Management Optimization, 2013, 9 (4) : 9831001. doi: 10.3934/jimo.2013.9.983 
[6] 
Chunlin Hao, Xinwei Liu. Global convergence of an SQP algorithm for nonlinear optimization with overdetermined constraints. Numerical Algebra, Control & Optimization, 2012, 2 (1) : 1929. doi: 10.3934/naco.2012.2.19 
[7] 
Miao Yu. A solution of TSP based on the ant colony algorithm improved by particle swarm optimization. Discrete & Continuous Dynamical Systems  S, 2019, 12 (4&5) : 979987. doi: 10.3934/dcdss.2019066 
[8] 
David Russell. Structural parameter optimization of linear elastic systems. Communications on Pure & Applied Analysis, 2011, 10 (5) : 15171536. doi: 10.3934/cpaa.2011.10.1517 
[9] 
M. S. Lee, B. S. Goh, H. G. Harno, K. H. Lim. On a twophase approximate greatest descent method for nonlinear optimization with equality constraints. Numerical Algebra, Control & Optimization, 2018, 8 (3) : 315326. doi: 10.3934/naco.2018020 
[10] 
JeanPaul Arnaout, Georges Arnaout, John El Khoury. Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated locationallocation problem. Journal of Industrial & Management Optimization, 2016, 12 (4) : 12151225. doi: 10.3934/jimo.2016.12.1215 
[11] 
K. T. Arasu, Manil T. Mohan. Optimization problems with orthogonal matrix constraints. Numerical Algebra, Control & Optimization, 2018, 8 (4) : 413440. doi: 10.3934/naco.2018026 
[12] 
Michal Kočvara, Jiří V. Outrata. Inverse truss design as a conic mathematical program with equilibrium constraints. Discrete & Continuous Dynamical Systems  S, 2017, 10 (6) : 13291350. doi: 10.3934/dcdss.2017071 
[13] 
Paul Popescu, Cristian Ida. Nonlinear constraints in nonholonomic mechanics. Journal of Geometric Mechanics, 2014, 6 (4) : 527547. doi: 10.3934/jgm.2014.6.527 
[14] 
Pikkala Vijaya Laxmi, Singuluri Indira, Kanithi Jyothsna. Ant colony optimization for optimum service times in a Bernoulli schedule vacation interruption queue with balking and reneging. Journal of Industrial & Management Optimization, 2016, 12 (4) : 11991214. doi: 10.3934/jimo.2016.12.1199 
[15] 
Mingyong Lai, Xiaojiao Tong. A metaheuristic method for vehicle routing problem based on improved ant colony optimization and Tabu search. Journal of Industrial & Management Optimization, 2012, 8 (2) : 469484. doi: 10.3934/jimo.2012.8.469 
[16] 
Bertrand Maury, Aude RoudneffChupin, Filippo Santambrogio, Juliette Venel. Handling congestion in crowd motion modeling. Networks & Heterogeneous Media, 2011, 6 (3) : 485519. doi: 10.3934/nhm.2011.6.485 
[17] 
Jesús Fabián López Pérez, Tahir Ekin, Jesus A. Jimenez, Francis A. Méndez Mediavilla. Riskbalanced territory design optimization for a Micro finance institution. Journal of Industrial & Management Optimization, 2017, 13 (5) : 118. doi: 10.3934/jimo.2018176 
[18] 
Inger Daniels, Catherine Lebiedzik. Existence and uniqueness of a structural acoustic model involving a nonlinear shell. Discrete & Continuous Dynamical Systems  S, 2008, 1 (2) : 243252. doi: 10.3934/dcdss.2008.1.243 
[19] 
H. T. Banks, R.C. Smith. Feedback control of noise in a 2D nonlinear structural acoustics model. Discrete & Continuous Dynamical Systems  A, 1995, 1 (1) : 119149. doi: 10.3934/dcds.1995.1.119 
[20] 
M. Delgado Pineda, E. A. Galperin, P. Jiménez Guerra. MAPLE code of the cubic algorithm for multiobjective optimization with box constraints. Numerical Algebra, Control & Optimization, 2013, 3 (3) : 407424. doi: 10.3934/naco.2013.3.407 
2017 Impact Factor: 0.994
Tools
Metrics
Other articles
by authors
[Back to Top]