An effect of chaos grasshopper optimization algorithm for protection of network infrastructure

Grasshopper Optimization Algorithm: Theory, Variants, and Applications

“…The effectiveness of NBGOA was evaluated using 20 datasets with various sizes taken from the UCI datasets repository in comparison with five well-regarded optimization techniques in the feature selection field. Simulation results revealed that BGOA [78] NBGOA [79] BGOA [67] ECGOAs [80] LMGOA [81] ECGOA [82] CGOA [83] CGOA [84] SFECGOAs [85] OLCGOA [86] ECGOAs [87] ECAGOA [88] IGOA [70] EGOA [89] PGOA [90] LGOA [91] IGOA [92] AGOA [93] MI-LFGOA [94] LGOA [95] GOA_EPD [65] DJGOA [96] DQBGOA_MR [97] Fuzzy GOA [98] GO-FLC [99] EGOA-FC [100] AGOA [69] AGOA [101] GHO [102] self-adaptive GOA [103] OGOA [104] OBLGOA [105] IGOA [106] MOGOA [75] MOGOA [76] MOGOA [66] MOGOA [107] MOGOA [108] MOGOA [109] LWSGOA [110] MGOA [111] GOFS [112] PCA-GOA [113] OGOA [114] IGOA [115] Fractional-GOA…”

Hybridization of Grasshopper Optimization Algorithm With Genetic Algorithm for Solving System of Non-Linear Equations

“…But, GOA has some limitations such as: 1) unbalancing between the processes of exploitation and exploration; 2) convergence speed is unstable; and 3) may be fall into the local optimum. So, there are several hybrid algorithms between GOA and other PBAs have been proposed in the literature [52][53][54][55][56][57][58][59]. In [52], the authors proposed a dynamic population quantum binary GOA based on shared knowledge and a rough set theory for the selection of features; where GOA was improved by the quantum method.…”

“…While, In [53], Singh and Prakashthe optimized multiple optical network units (ONUs) placement in Fiber-Wireless (FiWi) access network using two recent optimization algorithms, HHO and GOA. Dwivedi et al proposed in [54] a new technique for the selection of features by combining the feature Selection Ensemble and the chaotic adaptive GOA. The chaos principle in GOA has been used to create a uniformly distributed population to boost the efficiency of the initial populations, control the capacity to look for new space referred to as exploration, and use existing space referred to as exploitation in the optimization process.…”

“…Finally, in [59], Alphonsa and Sundaram have used a hybrid algorithm for the data sanitation and restoration process, known as the grasshopper optimization with GA. These hybrid algorithms [52][53][54][55][56][57][58][59] aim to enhance GOA by generating a uniformly distributed population, improving the search scope, achieving good balance between exploration (the ability to search for new space) and exploitation (use existing space), producing a mature convergence rate or reducing the computational time.…”

Steady-State Sine Cosine Genetic Algorithm Based Chaotic Search for Nonlinear Programming and Engineering Applications

“…Recently, the mathematics of chaos theory has been used to improve various optimization methods. So, most researchers incorporate chaotic maps with the optimization techniques in order to get the global solutions of complex problems [53][54][55] and accelerate the convergence to the optimal solution such as adaptive firefly algorithm with chaos [56], Chaosenhanced cuckoo search optimization algorithm [57], chaos game optimization [58], chaos grasshopper optimization algorithm [59], chaotic fruit fly optimization algorithm [60] and chaos-enhanced bat algorithm [61].…”