Genetic Cuckoo Optimization Algorithm (GCOA)

Rashad, M. Z.; Keshk, Arabi; El-Dosuky, M. A.; Kamal, Murshid

doi:10.5120/15552-4187

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…Combining meta-heuristic with other correctional systems, the perceived halfbreed meta-heuristic gives increased productivity and greater adaptability when managing genuine world and enormous scale issues. On this basis, crossover meta-heuristics use different calculation properties [6], [7], [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25]. All half and half meta-heuristic methods can be performed in mass alloys or even in integrated mixtures [8].…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Bandwidth Optimization for Vertical Handoff using Hybrid Cuckoo Search and Genetic Algorithm Scheme

Khurana

Jha

Gupta

2022

J. Phys.: Conf. Ser.

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Future remote systems should have the option to handle the gain in a different system state. One of the most of the time tried issues for coordination is the vertical handoff, which is an option to handoff portable hubs between different systems. While customary handoff codes are based on quality checks, vertical handoffs must assess additional factors, for example, funding costs, proposed governance, systematic location, and customer learning. In this paper, some improvements are proposed for the implementation of vertical handoff option calculations aimed at increasing the nature of the administration experienced by each customer. Firstly, talk about the idea of alignment-based handoff is done. At that point, cost efficiency can be achieved by sending decisions on the target systems depending on the classification of the customer and the measurements provided by the system. Finally, a demonstration investigation suggests that the proposed reforms can achieve significant gains like governance and the productive use of assets. In the present work, two other half-schemes are proposed using the cuckoo search calculation and the genealogical calculation. In the two mixing plots, the calculation consists of two steps: the primary stage, which examines the location of the cuckoo search (CS), or the genetic algorithm (GA). In the subsequent stage, to improve worldwide pursuit and dispose of catching into a few neighbourhood optima is done. Reproducibility results and testing with old-time CS and GA calculations confirm the feasibility of the proposed computation in designing various benchmark correction capabilities.

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