GMO: geometric mean optimizer for solving engineering problems

[1]  G. Theraulaz,et al.  Termite life cycle optimizer , 2022, Expert Syst. Appl..

[2]  Tareq M. Shami,et al.  Single candidate optimizer: a novel optimization algorithm , 2022, Evolutionary Intelligence.

[3]  Thanh Sang-To,et al.  A new metaheuristic optimization based on K-means clustering algorithm and its application to structural damage identification , 2022, Knowl. Based Syst..

[4]  A. Gandomi,et al.  Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer , 2021, Expert Syst. Appl..

[5]  A. K. Bhunia,et al.  Design of an efficient hybridized CS-PSO algorithm and its applications for solving constrained and bound constrained structural engineering design problems , 2021, Results in Control and Optimization.

[6]  Amir H. Gandomi,et al.  The Arithmetic Optimization Algorithm , 2021, Computer Methods in Applied Mechanics and Engineering.

[7]  Dalia Yousri,et al.  Aquila Optimizer: A novel meta-heuristic optimization algorithm , 2021, Comput. Ind. Eng..

[8]  Seyed Mohammad Mirjalili,et al.  Flow Direction Algorithm (FDA): A Novel Optimization Approach for Solving Optimization Problems , 2021, Comput. Ind. Eng..

[9]  Omid Bozorg Haddad,et al.  Gradient-based optimizer: A new metaheuristic optimization algorithm , 2020, Inf. Sci..

[10]  Asoke Kumar Bhunia,et al.  A new QPSO based hybrid algorithm for constrained optimization problems via tournamenting process , 2020, Soft Comput..

[11]  Seyedali Mirjalili,et al.  Equilibrium optimizer: A novel optimization algorithm , 2020, Knowl. Based Syst..

[12]  Seyed Taghi Akhavan Niaki,et al.  A new hybrid algorithm to solve bound-constrained nonlinear optimization problems , 2020, Neural Computing and Applications.

[13]  Sinan Q. Salih,et al.  A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer , 2019, Neural Computing and Applications.

[14]  Hossein Moayedi,et al.  A Novel Swarm Intelligence—Harris Hawks Optimization for Spatial Assessment of Landslide Susceptibility , 2019, Sensors.

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

[16]  Zubaidah Ismail,et al.  A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems , 2019, Int. J. Comput. Math..

[17]  Harish Garg,et al.  A hybrid GSA-GA algorithm for constrained optimization problems , 2019, Inf. Sci..

[18]  Diego Oliva,et al.  An improved Opposition-Based Sine Cosine Algorithm for global optimization , 2017, Expert Syst. Appl..

[19]  Hossam Faris,et al.  Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems , 2017, Adv. Eng. Softw..

[20]  Aboul Ella Hassanien,et al.  Whale Optimization Algorithm and Moth-Flame Optimization for multilevel thresholding image segmentation , 2017, Expert Syst. Appl..

[21]  Jacek Czerniak,et al.  AAO as a new strategy in modeling and simulation of constructional problems optimization , 2017, Simul. Model. Pract. Theory.

[22]  Kaveh Madani,et al.  f-MOPSO: An alternative multi-objective PSO algorithm for conjunctive water use management , 2017 .

[23]  Adil Baykasoglu,et al.  Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems - Part 1: Unconstrained optimization , 2015, Appl. Soft Comput..

[24]  Andrew Lewis,et al.  The Whale Optimization Algorithm , 2016, Adv. Eng. Softw..

[25]  Najeh Ben Guedria,et al.  Improved accelerated PSO algorithm for mechanical engineering optimization problems , 2016, Appl. Soft Comput..

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

[27]  Adil Baykasoglu,et al.  Adaptive firefly algorithm with chaos for mechanical design optimization problems , 2015, Appl. Soft Comput..

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

[29]  R. J. Kuo,et al.  The gradient evolution algorithm: A new metaheuristic , 2015, Inf. Sci..

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

[31]  Ali Kaveh,et al.  Colliding bodies optimization: A novel meta-heuristic method , 2014 .

[32]  A. Gandomi Interior search algorithm (ISA): a novel approach for global optimization. , 2014, ISA transactions.

[33]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[34]  Ardeshir Bahreininejad,et al.  Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems , 2013, Appl. Soft Comput..

[35]  Abdolreza Hatamlou,et al.  Black hole: A new heuristic optimization approach for data clustering , 2013, Inf. Sci..

[36]  A. Kaveh,et al.  A new meta-heuristic method: Ray Optimization , 2012 .

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

[38]  Yong Wang,et al.  Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization , 2010, Appl. Soft Comput..

[39]  Siamak Talatahari,et al.  An improved ant colony optimization for constrained engineering design problems , 2010 .

[40]  Mahamed G. H. Omran,et al.  Constrained optimization using CODEQ , 2009 .

[41]  Jing Wang,et al.  Space transformation search: a new evolutionary technique , 2009, GEC '09.

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

[43]  Wenjian Luo,et al.  Differential evolution with dynamic stochastic selection for constrained optimization , 2008, Inf. Sci..

[44]  Carlos A. Coello Coello,et al.  An empirical study about the usefulness of evolution strategies to solve constrained optimization problems , 2008, Int. J. Gen. Syst..

[45]  M. Mahdavi,et al.  ARTICLE IN PRESS Available online at www.sciencedirect.com , 2007 .

[46]  M. Fesanghary,et al.  An improved harmony search algorithm for solving optimization problems , 2007, Appl. Math. Comput..

[47]  Ling Wang,et al.  A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization , 2007, Appl. Math. Comput..

[48]  Ling Wang,et al.  An effective co-evolutionary differential evolution for constrained optimization , 2007, Appl. Math. Comput..

[49]  Ling Wang,et al.  An effective co-evolutionary particle swarm optimization for constrained engineering design problems , 2007, Eng. Appl. Artif. Intell..

[50]  George G. Dimopoulos,et al.  Mixed-variable engineering optimization based on evolutionary and social metaphors , 2007 .

[51]  K. Lee,et al.  A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice , 2005 .

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

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

[54]  C. Coello TREATING CONSTRAINTS AS OBJECTIVES FOR SINGLE-OBJECTIVE EVOLUTIONARY OPTIMIZATION , 2000 .

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

[56]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[57]  Kalyanmoy Deb,et al.  Optimal design of a welded beam via genetic algorithms , 1991 .

[58]  E. Sandgren,et al.  Nonlinear Integer and Discrete Programming in Mechanical Design Optimization , 1990 .

[59]  K. M. Ragsdell,et al.  Optimal Design of a Class of Welded Structures Using Geometric Programming , 1976 .