Designing problem-specific operators for solving the Cell Switch-Off problem in ultra-dense 5G networks with hybrid MOEAs

Galeano-Brajones, Jesús; Luna-Valero, Francisco; Carmona-Murillo, Javier; Cano, Pablo H. Zapata; Valenzuela-Valdés, Juan F.

doi:10.1016/j.swevo.2023.101290

Cited by 7 publications

(1 citation statement)

References 49 publications

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“…The mutation phase uses a predetermined rate of 1/L, where L is the number of decision variables (the chromosome length). This rate is widely used in the related literature [29] and is known to provide significant diversity. FLECO applies this mutation rate to every gene in each chromosome, ensuring that, when applicable, the new allele is different from the current one.…”

Section: Crossover and Mutation Operatorsmentioning

confidence: 99%

Fast, Lightweight, and Efficient Cybersecurity Optimization for Tactical–Operational Management

et al. 2023

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The increase in frequency and complexity of cyberattacks has heightened concerns regarding cybersecurity and created an urgent need for organizations to take action. To effectively address this challenge, a comprehensive and integrated approach is required involving a cross-functional cybersecurity workforce that spans tactical and operational levels. In this context there can be various combinations of cybersecurity actions that affect different functional domains and that allow for meeting the established requirements. In these cases, agreement will be needed, but finding high-quality combinations requires analysis from all perspectives on a case-by-case basis. With a large number of cybersecurity factors to consider, the size of the search space of potential combinations becomes unmanageable without automation. To solve this issue, we propose Fast, Lightweight, and Efficient Cybersecurity Optimization (FLECO), an adaptive, constrained, and multi-objective genetic algorithm that reduces the time required to identify sets of high-quality cybersecurity actions. FLECO enables productive discussions on viable solutions by the cross-functional cybersecurity workforce within an organization, fostering managing meetings where decisions are taken and boosting the overall cybersecurity management process. Our proposal is novel in its application of evolutionary computing to solve a managerial issue in cybersecurity and enhance the tactical–operational cybersecurity management process.

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Section: Crossover and Mutation Operatorsmentioning

confidence: 99%