Dynamic Beam Scheduling of Multibeam Low Earth Orbit Satellites Based on an Enhanced Artificial Bee Colony Algorithm DOI Creative Commons
Debin Wei, Dongdong Zheng,

Chengsheng Pan

et al.

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 115424 - 115434

Published: Jan. 1, 2022

The application of beam-hopping technology to low earth orbit satellites can effectively achieve flexible allocation and efficient utilization on-board resources. Considering that the power resources on are limited, electromagnetic environment is complex changeable, terminal distribution service requirements highly dynamic. We established model, priority model multibeam resource scheduling under constraints beam bandwidth, power, priorities, etc. To solve catastrophic problem a large solution space in improve convergence algorithm, we propose an enhanced artificial bee colony algorithm. optimization strategy improves process population initialization, updates, search for global optimal solution. simulation results show cochannel interference utilization, algorithm always converges objective function at fastest speed, which proves has high applicability dynamic characteristics LEO satellites. In addition, obtain solution, thus, it ensure fairness effectiveness completion.

Language: Английский

Information-Theory-based Nondominated Sorting Ant Colony Optimization for Multiobjective Feature Selection in Classification DOI
Ziqian Wang, Shangce Gao, MengChu Zhou

et al.

IEEE Transactions on Cybernetics, Journal Year: 2022, Volume and Issue: 53(8), P. 5276 - 5289

Published: Aug. 22, 2022

Feature selection (FS) has received significant attention since the use of a well-selected subset features may achieve better classification performance than that full in many real-world applications. It can be considered as multiobjective optimization consisting two objectives: 1) minimizing number selected and 2) maximizing performance. Ant colony (ACO) shown its effectiveness FS due to problem-guided search operator flexible graph representation. However, there lacks an effective ACO-based approach for handle problematic characteristics originated from feature interactions highly discontinuous Pareto fronts. This article presents Information-theory-based Nondominated Sorting ACO (called INSA) solve aforementioned difficulties. First, probabilistic function is modified based on information theory identify importance features; second, new strategy designed construct solutions; third, novel pheromone updating devised ensure high diversity tradeoff solutions. INSA's compared with four machine-learning-based methods, representative single-objective evolutionary algorithms, six state-of-the-art ones 13 benchmark datasets, which consist both low high-dimensional samples. The empirical results verify INSA able obtain solutions using whose count similar or less those obtained by peers.

Language: Английский

Citations

62

A hybrid task allocation approach for multi-UAV systems with complex constraints: a market-based bidding strategy and improved NSGA-III optimization DOI
Mi Yang, Baichuan Zhang,

Zhifu Shi

et al.

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(4)

Published: Feb. 26, 2025

Language: Английский

Citations

1

A task allocation algorithm for a swarm of unmanned aerial vehicles based on bionic wolf pack method DOI
Ziheng Wang, Jianlei Zhang

Knowledge-Based Systems, Journal Year: 2022, Volume and Issue: 250, P. 109072 - 109072

Published: May 23, 2022

Language: Английский

Citations

35

A novel hybrid Coyote–Particle Swarm Optimization Algorithm for three-dimensional constrained trajectory planning of Unmanned Aerial Vehicle DOI
Himanshu Gupta, Om Prakash Verma

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 147, P. 110776 - 110776

Published: Aug. 26, 2023

Language: Английский

Citations

20

Cooperative task allocation for multi heterogeneous aerial vehicles using particle swarm optimization algorithm and entropy weight method DOI
Shaobo Zhai, Guangwen Li,

Guo Wu

et al.

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 148, P. 110918 - 110918

Published: Oct. 9, 2023

Language: Английский

Citations

19

Cooperative task allocation method for air-sea heterogeneous unmanned system with an application to ocean environment information monitoring DOI
Wenhao Bi, Mengqi Zhang, Hao Chen

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 309, P. 118496 - 118496

Published: June 19, 2024

Language: Английский

Citations

7

Multi-objective Ant Colony Optimization: Review DOI
Mohammed A. Awadallah, Sharif Naser Makhadmeh, Mohammed Azmi Al‐Betar

et al.

Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: 32(2), P. 995 - 1037

Published: Sept. 10, 2024

Language: Английский

Citations

6

Coverage Path Planning of UAV Based on Linear Programming—Fuzzy C-Means with Pigeon-Inspired Optimization DOI Creative Commons
Jiang Yan,

Tingting Bai,

Daobo Wang

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(2), P. 50 - 50

Published: Feb. 4, 2024

In contrast to rotorcraft, fixed-wing unmanned aerial vehicles (UAVs) encounter a unique challenge in path planning due the necessity of accounting for turning radius constraint. This research focuses on coverage planning, aiming determine optimal trajectories UAVs thoroughly explore designated areas interest. To address this challenge, Linear Programming—Fuzzy C-Means with Pigeon-Inspired Optimization algorithm (LP-FCMPIO) is proposed. Initially considering constraint, linear-programming-based model UAV established. Subsequently, partition multiple effectively, an improved fuzzy clustering introduced. Employing pigeon-inspired optimization as final step, approximately solution sought. Simulation experiments demonstrate that LP-FCMPIO, when compared traditional FCM, achieves more balanced effect. Additionally, PIO, planned flight paths display task areas, 27.5% reduction number large maneuvers. The experimental results provide validation effectiveness proposed algorithm.

Language: Английский

Citations

5

Two-stage task allocation for multiple construction robots using an improved genetic algorithm DOI

Xiaotian Ye,

Hongling Guo,

Zhubang Luo

et al.

Automation in Construction, Journal Year: 2024, Volume and Issue: 165, P. 105583 - 105583

Published: June 26, 2024

Language: Английский

Citations

5

Heterogeneous Fleets for Green Vehicle Routing Problem With Traffic Restrictions DOI
Heng Wang, Menghan Li, Zhenyu Wang

et al.

IEEE Transactions on Intelligent Transportation Systems, Journal Year: 2022, Volume and Issue: 24(8), P. 8667 - 8676

Published: Aug. 25, 2022

Suffering from environmental distress like carbon emissions, traffic restrictions have been enforced extensively in distribution logistics. Reasonable arrangement of urban freight transportation can effectively improve efficiency, reduce costs, and alleviate the impact In response to increasingly stringent restrictions, we establish a multi-objective optimization model, including minimum distributions emissions. Given that limits battery capacity cargo capacity, build green vehicle routing problem with soft time windows (GVRPTW) model heterogenous fleets. this study, three different factors, is restricted area, travel vehicles, tax prices, are discussed details. order solve NP-hard propose an improved ant colony algorithm (IACO) by optimizing state transition probability, verifies worth algorithm. The experimental results explore impacts restriction policies on formulation scheme offer reference opinions for government formulate reasonable better guide logistics enterprises

Language: Английский

Citations

17