Application of swarm intelligence optimization algorithms in image processing: A comprehensive review of analysis, synthesis, and optimization

M Xu, L Cao, D Lu, Z Hu, Y Yue - Biomimetics, 2023‏ - mdpi.com
Image processing technology has always been a hot and difficult topic in the field of artificial
intelligence. With the rise and development of machine learning and deep learning …

A modified equilibrium optimizer using opposition-based learning and novel update rules

Q Fan, H Huang, K Yang, S Zhang, L Yao… - Expert Systems with …, 2021‏ - Elsevier
Equilibrium Optimizer (EO) is a newly developed physics-based metaheuristic algorithm that
is based on control volume mass balance models, and has shown competitive performance …

Automated congressional redistricting

HA Levin, SA Friedler - Journal of Experimental Algorithmics (JEA), 2019‏ - dl.acm.org
Every 10 years, when states are forced to redraw their congressional districts, the process is
intensely partisan, and the outcome is rarely fair and democratic. In the past few decades …

Bio-inspired methods modeled for respiratory disease detection from medical images

M Woźniak, D Połap - Swarm and evolutionary computation, 2018‏ - Elsevier
Medicine is an important venue for practical applications of science. A fusion of
mathematical modeling and programming into computer methods makes a great support for …

Multi-agent coalition formation by an efficient genetic algorithm with heuristic initialization and repair strategy

M Guo, B **n, J Chen, Y Wang - Swarm and Evolutionary Computation, 2020‏ - Elsevier
In multi-agent systems (MAS), the coalition formation (CF) is an important problem focusing
on allocating agents to different tasks. In this paper, three specific CF problems are …

Preference-based cone contraction algorithms for interactive evolutionary multiple objective optimization

M Kadziński, MK Tomczyk, R Słowiński - Swarm and Evolutionary …, 2020‏ - Elsevier
We introduce a family of interactive evolutionary algorithms for Multiple Objective
Optimization (MOO). In the phase of preference elicitation, a Decision Maker (DM) is asked …

Many-objective sectorization for last-mile delivery optimization: A decision support system

G Torres, T Fontes, AM Rodrigues, P Rocha… - Expert Systems with …, 2024‏ - Elsevier
The efficient last-mile delivery of goods involves complex challenges in optimizing driver
sectors and routes. This problem tends to be large-scale and involves several criteria to …

Multi-objective cellular particle swarm optimization for wellbore trajectory design

J Zheng, C Lu, L Gao - Applied Soft Computing, 2019‏ - Elsevier
Wellbore trajectory design is a determinant issue in drilling engineering. The criteria to
evaluate a wellbore trajectory are summarized as the total trajectory length, the torque and …

Multi-objective optimization for multi-depot heterogeneous first-mile transportation system considering requests' preference ranks for pick-up stops

J Ren, W **, W Wu - Transportmetrica A: Transport Science, 2023‏ - Taylor & Francis
The first-mile transportation system connects scattered requests in residential areas to mass
transit networks and provides convenient and high-quality travelling services. The …

Evaluation of the absolute forms of cost functions in optimization using a novel evolutionary algorithm

A Mohammadi, N Nariman-Zadeh, M Payan, A Jamali - Soft Computing, 2023‏ - Springer
Many ordinary approaches in optimization are mathematical-based. Due to the limitations of
such methods, optimal problems have been commonly defined in single-objective and …