Anti-coronavirus optimization algorithm

Abstract

This paper introduces a new swarm intelligence strategy, anti-coronavirus optimization (ACVO) algorithm. This algorithm is a multi-agent strategy, in which each agent is a person that tries to stay healthy and slow down the spread of COVID-19 by observing the containment protocols. The algorithm composed of three main steps: social distancing, quarantine, and isolation. In the social distancing phase, the algorithm attempts to maintain a safe physical distance between people and limit close contacts. In the quarantine phase, the algorithm quarantines the suspected people to prevent the spread of disease. Some people who have not followed the health protocols and infected by the virus should be taken care of to get a full recovery. In the isolation phase, the algorithm cared for the infected people to recover their health. The algorithm iteratively applies these operators on the population to find the fittest and healthiest person. The proposed algorithm is evaluated on standard multi-variable single-objective optimization problems and compared with several counterpart algorithms. The results show the superiority of ACVO on most test problems compared with its counterparts.

An approach for DoS attack detection in cloud computing using sine cosine anti coronavirus optimized deep maxout network

“…The existing attack detection methods, such as RNN (Theja and Shyam, 2021), Naive AE+DNN (Bhardwaj et al , 2020), TEHO-DBN (Velliangiri et al , 2021) and V-ELM (Kushwah and Ranga, 2020), are considered for comparing the effectiveness of the developed SCACVO-based DMN approach. Moreover, the optimization techniques, including Spider Monkey Optimization (SMO) (Bansal et al , 2014), Chicken Swarm Optimization (CSO) (Meng et al , 2014), Sine Cosine Optimization (SCA) (Mirjalili, 2016), Anti Corona Virus Optimization (ACVO) (Emami, 2021) methods, are included for comparing the effectiveness of devised optimization model.…”

“…The DMN (Sun et al , 2018) is used for the attack detection process, and the DMN is trained by devised SCACVO algorithm. Accordingly, the designed SCACVO model is newly designed by incorporating SCA (Mirjalili, 2016) and ACVO method (Emami, 2021). Besides, the DMN detects the augmented data as attacker or genuine.…”

“…The DMN is trained by means of the SCACVO model, which was invented by incorporating the ACVO model and SCA. The ACVO (Emami, 2021) scheme is a multi-variable single objective optimization model, which is inspired by Coronavirus disease precautions, such as quarantine, isolation and social distancing. The ACVO approach is not effective for resolving engineering issues.…”

ACO-KELM: Anti Coronavirus Optimized Kernel-based Softplus Extreme Learning Machine for classification of skin cancer

“…The AVCO ( Emami, 2022 ; Muthuperumal et al, 2022) starts the operation by initializing the parameters and generating the solution. Quarantine, isolation, and social distancing are the three operators used for updating the population.…”

A Multi–Objective Gaining–Sharing Knowledge-Based Optimization Algorithm for Solving Engineering Problems

“…The dynastic optimization algorithm [44] is based on the social behavior of human dynasties. Finally, there is anticoronavirus optimization [45]. All these human-related algorithms have been used to solve different optimization problems.…”