A Phase Angle-Modulated Bat Algorithm with Application to Antenna Topology Optimization
Source abstract
Abstract
This paper proposes a phase angle-modulated bat algorithm (P-AMBA) for high-dimensional binary optimization. The idea was to reduce the optimization time by introducing angle modulation technology to reduce the optimization dimensions. Different from the original angle-modulated bat algorithm (AMBA), the control of the trigonometric generating function cosine wave is by introducing new parameters, thereby improving the perturbation ability of the function curve near the x-axis. P-AMBA can explore more 0/1 solutions, and it has advantages in optimizing convergence speed and global search capabilities. The numerical results of the 0–1 knapsack problem tests show that P-AMBA is superior to the contrast algorithms on optimization ability and optimization time. Finally, the experimental result of a compact dual-band planar monopole antenna design showed the effectiveness of P-AMBA in engineering applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Metaheuristic Optimization Algorithms Research · Antenna Design and Optimization · Advanced Multi-Objective Optimization Algorithms
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Computer Science and Engineering, Central South University, Changsha 410083, China
School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China
Funding
National Natural Science Foundation of China · Natural Science Foundation of Hunan Province · Fundamental Research Funds for the Central Universities
References (43)
Show source-provided references
1. An Adaptive-PSO-Based Self-Organizing RBF Neural Network10.1109/TNNLS.2016.2616413 ↗
2. Efficient mixture model for clustering of sparse high dimensional binary data10.1007/s10618-019-00635-1 ↗
3. Linear Dimensionality Reduction for Margin-Based Classification: High-Dimensional Data and Sensor Networks10.1109/TSP.2011.2123891 ↗
4. Robust Dynamic Multi-Objective Vehicle Routing Optimization Method10.1109/TCBB.2017.2685320 ↗
5. Design of High-Isolation Wideband Dual-Polarized Compact MIMO Antennas With Multiobjective Optimization10.1109/TAP.2017.2784446 ↗
6. Metaheuristics: From Design to Implementation
7. A new local search based hybrid genetic algorithm for feature selection10.1016/j.neucom.2011.03.034 ↗
8. Particle Swarm Optimization of Microstrip Antennas for Wireless Communication Systems10.1109/TAP.2013.2281517 ↗
9. A hybrid approach of differential evolution and artificial bee colony for feature selection10.1016/j.eswa.2016.06.004 ↗
10. DisABC: A new artificial bee colony algorithm for binary optimization10.1016/j.asoc.2011.08.038 ↗
11. Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems10.1007/s00521-015-1920-1 ↗
12. Fireworks Algorithm for Optimization
13. Brain Storm Optimization Algorithm
14. A New Heuristic Optimization Algorithm: Harmony Search10.1177/003754970107600201 ↗
15. Moth search algorithm: A bio-inspired metaheuristic algorithm for global optimization problems10.1007/s12293-016-0212-3 ↗
16. Yang, X.-S. (2010). A New Metaheuristic Bat-Inspired Algorithm. Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), Springer.10.1007/978-3-642-12538-6_6 ↗
17. A Smart Bat Algorithm for Wireless Sensor Network Deployment in 3-D Environment10.1109/LCOMM.2018.2861766 ↗
18. Data Clustering Method Based on Improved Bat Algorithm With Six Convergence Factors and Local Search Operators10.1109/ACCESS.2020.2991091 ↗
19. Bi-Population Based Discrete Bat Algorithm for the Low-Carbon Job Shop Scheduling Problem10.1109/ACCESS.2019.2892826 ↗
20. Optimal Reactive Power Dispatch Using Chaotic Bat Algorithm10.1109/ACCESS.2020.2982988 ↗
21. BAT algorithm inspired retinal blood vessel segmentation10.1049/iet-ipr.2017.1266 ↗
22. Binary bat algorithm10.1007/s00521-013-1525-5 ↗
23. Hembecker, F., Lopes, H.S., and Godoy, W. (2007). Particle Swarm Optimization for the Multidimensional Knapsack Problem. International Conference on Adaptive and Natural Computing Algorithms, Springer.10.1007/978-3-540-71618-1_40 ↗
24. Guo, S.-S., Wang, J.-S., and Ma, X.-X. (2019). Improved Bat Algorithm Based on Multipopulation Strategy of Island Model for Solving Global Function Optimization Problem. Comput. Intell. Neurosci.10.1155/2019/6068743 ↗
25. Xue, J., Xiao, J., and Zhu, J. (2019, January 16–18). Binary Fireworks Algorithm for 0-1 Knapsack Problem. Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM), Dublin, Ireland.10.1109/AIAM48774.2019.00051 ↗
26. A Binary Multi-Scale Quantum Harmonic Oscillator Algorithm for 0–1 Knapsack Problem With Genetic Operator10.1109/ACCESS.2019.2942340 ↗
27. Binary Bat Algorithm: On The Efficiency of Mapping Functions When Handling Binary Problems Using Continuous-variable-based Metaheuristics
28. Amplitude Angle Modulated Bat Algorithm With Application to Zero-One Knapsack Problem10.1109/ACCESS.2019.2901988 ↗
29. Miniaturization of a Dual-Band Wearable Antenna for WBAN Applications10.1109/LAWP.2020.3005658 ↗
30. A Small Symmetric-Slit-Shaped and Annular Slotted BeiDou Antenna With Stable Phase Center10.1109/LAWP.2017.2778219 ↗
31. Creation of new shapes for resonant microstrip structures by means of genetic algorithms10.1049/el:19971017 ↗
32. Guariglia, E. (2016). Entropy and Fractal Antennas. Entropy, 18.10.3390/e18030084 ↗
33. Guariglia, E. (2019). Primality, Fractality, and Image Analysis. Entropy, 21.10.3390/e21030304 ↗
34. Design of a fragment-type UHF RFID tag integrated into printed circuit board10.1002/mop.31631 ↗
35. Design of Compact High-Isolation MIMO Antenna With Multiobjective Mixed Optimization Algorithm10.1109/LAWP.2020.2997874 ↗
36. Optimization Using Simulated Annealing
37. Proakis, J.G., Salehi, M., Zhou, N., and Li, X. (1994). Communication Systems Engineering, Prentice Hall.
38. Pampara, G., Franken, N., and Engelbrecht, A. (2005). Combining Particle Swarm Optimisation with angle modulation to solve binary problems. IEEE Congr. Evol. Comput., 89–96.10.1109/CEC.2005.1554671 ↗
39. Critical considerations on angle modulated particle swarm optimisers10.1007/s11721-015-0114-x ↗
40. Discrete-Variable Extremum Problems10.1287/opre.5.2.266 ↗
41. A Discrete Improved Artificial Bee Colony Algorithm for 0–1 Knapsack Problem10.1109/ACCESS.2019.2930638 ↗
42. A novel discrete whale optimization algorithm for solving knapsack problems10.1007/s10489-020-01722-3 ↗
43. Multiband Single-Layer Frequency Selective Surface Designed by Combination of Genetic Algorithm and Geometry-Refinement Technique10.1109/TAP.2004.835289 ↗