2020
DOI: 10.3390/app10196858
|View full text |Cite
|
Sign up to set email alerts
|

SETNDS: A SET-Based Non-Dominated Sorting Algorithm for Multi-Objective Optimization Problems

Abstract: Non‐dominated sorting, used to find pareto solutions or assign solutions to differentfronts, is a key but time‐consuming process in multi‐objective evolutionary algorithms (MOEAs).The best‐case and worst‐case time complexity of non‐dominated sorting algorithms currentlyknown are O(MNlogN) and O(MN2); M and N represent the number of objectives and the populationsize, respectively. In this paper, a more efficient SET‐based non‐dominated sorting algorithm,shorted to SETNDS, is proposed. The proposed algorithm can… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
3
2
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 8 publications
(3 citation statements)
references
References 29 publications
0
3
0
Order By: Relevance
“…Posteriori method includes Multi-Objective Evolutionary Algorithms (MOEA) and stochastic algorithms based on a random population. Some of the common examples of this technique are the Particle Swarm Optimization (PSO) and Non-Dominated Sorting Genetic Algorithm (NSGA) [19,20]. These techniques have broad applications in optimizing processes and devices related to different fields like manufacturing, aerospace, marine, and electrical power sectors [21,22,23,24].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Posteriori method includes Multi-Objective Evolutionary Algorithms (MOEA) and stochastic algorithms based on a random population. Some of the common examples of this technique are the Particle Swarm Optimization (PSO) and Non-Dominated Sorting Genetic Algorithm (NSGA) [19,20]. These techniques have broad applications in optimizing processes and devices related to different fields like manufacturing, aerospace, marine, and electrical power sectors [21,22,23,24].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Additionally, during network training, it is crucial to input data in accordance with the sequence of images captured by the UAV to meet the format requirements of the optical flow estimation channel. To address this limitation, future research efforts may prioritize the development of intelligent image processing [65] and sorting algorithms [66]. These advancements would enable automatic processing of out-of-order image inputs and harness the multi-view capabilities of drones to enhance occlusion modeling.…”
Section: Limitations and Perspectivementioning
confidence: 99%
“…Many non-dominated sorting algorithms explicitly make use of sorting in order to avoid the cost of dominance comparisons in at least one dimension [Zhang et al, 2015, Roy et al, 2016, Bao et al, 2017, Zhou et al, 2017, Xue et al, 2020, Moreno et al, 2020. However, only a few explicitly consider stability [Roy et al, 2016, Moreno et al, 2020.…”
Section: Correctness Of the Algorithmmentioning
confidence: 99%