Population-based optimization in structural engineering: a review

AR Kashani, CV Camp, M Rostamian, K Azizi… - Artificial Intelligence …, 2022 - Springer
Structural engineering is focused on the safe and efficient design of infrastructure. Projects
can range in size and complexity, many requiring massive amounts of materials and …

Structural optimization using multi-objective modified adaptive symbiotic organisms search

GG Tejani, N Pholdee, S Bureerat, D Prayogo… - Expert Systems with …, 2019 - Elsevier
Multiple objective structural optimization is a challenging problem in which suitable
optimization methods are needed to find optimal solutions. Therefore, to answer such …

An efficient k-NN-based rao optimization method for optimal discrete sizing of truss structures

HA Pham, VH Dang, TC Vu, BD Nguyen - Applied Soft Computing, 2024 - Elsevier
This study proposes a new method called k-nearest neighbor comparison (k-NNC) to
address the computational cost issue of truss optimization with discrete variables using …

[PDF][PDF] Genetic algorithm-based tabu search for optimal energy-aware allocation of data center resources

R Chandran, SR Kumar, N Gayathri - Soft Computing, 2020 - academia.edu
Cloud computing delivers practical solutions for long-term image archiving systems. Cloud
data centers consume enormous amounts of electrical energy that increases their …

Methodology for the projection of population pyramids based on monte Carlo simulation and genetic algorithms

P Quirós, FS Lasheras - Applied Intelligence, 2023 - Springer
The analysis of the evolution of population pyramids is crucial to study and tackle the
growing issue associated to the depopulation of different regions around the world. This task …

The “one-fifth rule” with rollbacks for self-adjustment of the population size in the (1+(λ, λ)) genetic algorithm

AO Bassin, MV Buzdalov, AA Shalyto - Automatic Control and Computer …, 2021 - Springer
Self-adjustment of parameters can significantly improve the performance of evolutionary
algorithms. A notable example is the (1+(λ, λ)) genetic algorithm, where adaptation of the …

Truss sizing optimum design using a metaheuristic approach: Connected banking system

M Nemati, Y Zandi, J Sabouri - Heliyon, 2024 - cell.com
Several methods have been used to solve structural optimum design problems since the
creation of a need for light weight design of structures and there is still no single method for …

The Genetic Algorithm on the Vertex Cover Problem: Crossover Helps Leaving Plateaus

M Buzdalov - 2022 IEEE Congress on Evolutionary …, 2022 - ieeexplore.ieee.org
Many discrete optimization problems feature plateaus, which are hard to evolutionary
algorithms due to the lack of fitness guidance. While higher mutation rates may assist in …

Правило «одной пятой» с возвратами для настройки размера популяции в генетическом алгоритме (1+(λ, λ))

АО Басин, МВ Буздалов… - Моделирование и анализ …, 2020 - mais-journal.ru
В данной работе предлагается модификация правила «одной пятой», существенно
снижающая отрицательные эффекты от его использования при их наличии …

[PDF][PDF] e “One-h Rule” with Rollbacks for Self-Adjustment of the Population Size in the (1+(,)) Genetic Algorithm

AO Bassin, MV Buzdalov, AA Shalyto - Modeling and Analysis of …, 2020 - mais-journal.ru
В данной работе предлагается модификация правила «одной пятой», существенно
снижающая отрицательные эффекты от его использования при их наличии …