Plant intelligence based metaheuristic optimization algorithms

S Akyol, B Alatas - Artificial Intelligence Review, 2017 - Springer
Classical optimization algorithms are insufficient in large scale combinatorial problems and
in nonlinear problems. Hence, metaheuristic optimization algorithms have been proposed …

Nonlinear equations solving with intelligent optimization algorithms: A survey

W Gong, Z Liao, X Mi, L Wang… - … System Modeling and …, 2021 - ieeexplore.ieee.org
Nonlinear Equations (NEs), which may usually have multiple roots, are ubiquitous in diverse
fields. One of the main purposes of solving NEs is to locate as many roots as possible …

Optimization of artificial intelligence system by evolutionary algorithm for prediction of axial capacity of rectangular concrete filled steel tubes under compression

HQ Nguyen, HB Ly, VQ Tran, TA Nguyen, TT Le… - Materials, 2020 - mdpi.com
Concrete filled steel tubes (CFSTs) show advantageous applications in the field of
construction, especially for a high axial load capacity. The challenge in using such structure …

Finding multiple roots of nonlinear equation systems via a repulsion-based adaptive differential evolution

W Gong, Y Wang, Z Cai, L Wang - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Finding multiple roots of nonlinear equation systems (NESs) in a single run is one of the
most important challenges in numerical computation. We tackle this challenging task by …

Energy-efficient uplink resource allocation in LTE networks with M2M/H2H co-existence under statistical QoS guarantees

A Aijaz, M Tshangini, MR Nakhai, X Chu… - IEEE Transactions …, 2014 - ieeexplore.ieee.org
Recently, energy efficiency in wireless networks has become an important objective. Aside
from the growing proliferation of smartphones and other high-end devices in conventional …

A discrete multi-objective fireworks algorithm for flowshop scheduling with sequence-dependent setup times

L He, W Li, Y Zhang, Y Cao - Swarm and Evolutionary Computation, 2019 - Elsevier
Multi-objective flow shop scheduling problem with sequence-dependent setup times
(MOFSP-SDST) is a class of important production scheduling problem with strong industry …

Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates

M Panahi, O Rahmati, F Rezaie, S Lee, F Mohammadi… - Catena, 2022 - Elsevier
Landslide susceptibility (LS) map** is an essential tool for landslide risk assessment. This
study aimed to provide a new approach with better performance for landslide map** and …

Solving nonlinear equations system with dynamic repulsion-based evolutionary algorithms

Z Liao, W Gong, X Yan, L Wang… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Nonlinear equations system (NES) arises commonly in science and engineering. Repulsion
techniques are considered to be the effective methods to locate different roots of NES. In …

A penalty-based differential evolution for multimodal optimization

Z Wei, W Gao, G Li, Q Zhang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
It is very difficult to locate multiple global optimal solutions (GOSs) of multimodal optimization
problems (MMOPs). To deal with this issue, a penalty-based multimodal optimization …

Solving multi-objective portfolio optimization problem using invasive weed optimization

AR Pouya, M Solimanpur, MJ Rezaee - Swarm and Evolutionary …, 2016 - Elsevier
Portfolio optimization is one of the important issues for effective and economic investment.
There is plenty of research in the literature addressing this issue. Most of these pieces of …