Reference No.

Author’s Name

Name of Technique

Problem Controlled

[44]

Fonseca, C.M. and Fleming, P.J. [1993]

(MOGA) Multi-Objective Genetic Algorithm

Optimization

[45]

Horn, J. et al. [1994]

(NPGA) Niched Pareto Genetic Algorithm

Multi-Objective Optimization

[46]

Srinivas, N. and Deb, K. [1995]

(NSGA) Non-Dominated Sorting Genetic Algorithms

Multi-Objective Optimization

[47]

Stutzle, T. [1998]

(PAS) Parallelization of Ant System

Combinatorial Optimization

[48]

Bullnheimer, B., Hartl, R.F. and Strauss, C. [1997]

(AS rank) Rank Based Ant System

TSP

[49]

Van den Bergh, F. and Engelbrecht, A. [2002]

(GCPSO) Guaranteed Convergence Particle Swarm Optimization

Convergence to Local Minimum

[50]

Yang, C. and Simon, D. [2005]

(HPSO) Hierarchical Particle Swarm Optimization

Better Solution

[51]

Janson, S. and Middenfort, M. [2006]

(NPSO) New Particle Swarm Optimization

Better Solution

[52]

Kim, D.H. et al.

[2007]

(HGA) Hybrid Genetic Algorithm

Global Optimization

[53]

Hu, X.M., Zhung, J. and Li, Y. [2008]

(COAC) Continuous Orthogonal Ant Colony

Continuous Optimizing Problems

[54]

Yu, B., Yang, Z-Z. and Yao, B.Z. [2009]

(IACO) Improved Ant Colony Optimization

Vehicle Routing

[55]

Ruhana, K. and Aljanaby, K.M.A. [2010]

(IMACO) Interacted Multiple Ant Colony Optimization

Different Instances of TSP

[56]

Taspnar, N. [2010]

(ABC-PTS) Partial Transmit Sequences (PTSs) Based on ABC

Peak-to-Average Power Ratio

[57]

El-Abd, M. [2011]

(OABC) ABC with the Concept of Opposition Number-Based Optimization

Black Box Optimization

[58]

Sonmez, M. [2011]

(ABC-AP) Artificial Bee Colony with Adaptive Penalty Function

Weight of Truss Structures

[59]

Gupta, D.K., Arora, Y. et al. [2012]

(RMACO) Recursive Multiple Ant Colony Optimization

Estimation of Parameters of a Function

[60]

Deepak, R. et al. [2014]

(HBMO) Honeybee Mating Optimization Algorithm

Test Case Optimization

[61]

Tsai, P.W. et al. [2014]

(IABC) Interactive Artificial Bee Colony Optimization

Numerical Optimization

[62]

Zheng, Y.J. [2015]

(WWO) Water Wave Optimization

Train Scheduling Problem

[63]

Mirjalili, S. and Lewis, A. [2016]

(WOA) Whale Optimization Algorithm

Multimodal Functions

[64]

Saremi, S., Mirjalili, S. and Lewis, A. [2017]

(GOA) Grasshopper Optimization Algorithm

Real Life Problems

[65]

Yu, H. et al. [2018]

(SHPSO) Surrogate-Assisted Hierarchical PSO

High-Dimensional Problems

[66]

Pierezan, J. and Dos Santos Coelho, L. [2018]

(COA) Coyote Optimization Algorithm

Global Optimization Problems

[67]

Khajeh, A., Ghasemi, M.R. and Arab, H.G. [2019]

(MPSO) Modified PSO with Novel Population Initialization

Benchmark Function Optimization

[68]

Shabani, A. et al. [2019]

(SAR) Search and Rescue Optimization

Single-Objective Continuous Optimization Problems

[69]

Hosseini, S.A., Hajipour, A. and Tavakoli, H. [2019]

(HAFPSO) Hunter-Attack Fractional-Order PSO

Optimum Design of Power Amplifier

[70]

Marzbali, A.G. [2020]

(BSSA) Bear Smell Search Algorithm

Real World Engineering Problems

[71]

Xiong, H., Qiu, B. and Liu, J. [2020]

(NMSPSO) Novel Multi-Swam PSO

Real-World Applications Problem

[72]

Dash, J., Dam, B. and Swain, R. [2020]

(HDEPSO) Hybrid Differential Evolution Particle Swarm Optimization

Sharp Edge FIR Filter (SEFIRF) Design Problem