scholarly journals D-MOSG: Discrete multi-objective shuffled gray wolf optimizer for multi-level image thresholding

2021 ◽  
Author(s):  
Murat Karakoyun ◽  
Şaban Gülcü ◽  
Halife Kodaz
Keyword(s):  
Gray Wolf ◽  
Image Thresholding ◽  
Multi Objective ◽  
Gray Wolf Optimizer ◽  
Multi Level

scholarly journals Application of AMOGWO in Multi-Objective Optimal Allocation of Water Resources in Handan, China

Water ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 63
Author(s):  
Su Li ◽  
Zhihong Yan ◽  
Jinxia Sha ◽  
Jing Gao ◽  
Bingqing Han ◽  
...  
Keyword(s):  
Water Resources ◽  
Optimal Allocation ◽  
Convergence Rates ◽  
High Reliability ◽  
Water Shortage ◽  
Gray Wolf ◽  
Total Water ◽  
Multi Objective ◽  
Comparison Results ◽  
Gray Wolf Optimizer

The reasonable allocation of water resources using different optimization technologies has received extensive attention. However, not all optimization algorithms are suitable for solving this problem because of its complexity. In this study, we applied an ameliorative multi-objective gray wolf optimizer (AMOGWO) to the problem. For AMOGWO, which is based on the multi-objective gray wolf optimizer, we improved the distance control parameter calculation method, added crowding degree for the archive, and optimized the selection mechanism for leader wolves. Subsequently, AMOGWO was used to solve the multi-objective optimal allocation of water resources in Handan, China, for 2035, with the maximum economic benefit and minimum social water shortage used as objective functions. The optimal results obtained indicate a total water demand in Handan of 2740.43 × 106 m3, total water distribution of 2442.23 × 106 m3, and water shortage of 298.20 × 106 m3, which is consistent with the principles of water resource utilization in Handan. Furthermore, comparison results indicate that AMOGWO has substantially enhanced convergence rates and precision compared to the non-dominated sorting genetic algorithm II and the multi-objective particle swarm optimization algorithm, demonstrating relatively high reliability and applicability. This study thus provides a new method for solving the multi-objective optimal allocation of water resources.

Hyperspectral Multi-level Image Thresholding using Qutrit Genetic Algorithm

2021 ◽  
pp. 115107
Author(s):  
Tulika Dutta ◽  
Sandip Dey ◽  
Siddhartha Bhattacharyya ◽  
Somnath Mukhopadhyay ◽  
Prasun Chakrabarti
Keyword(s):  
Genetic Algorithm ◽  
Image Thresholding ◽  
Multi Level

Multi-objective optimization of two-dimensional phoxonic crystals with multi-level substructure scheme

2016 ◽  
Vol 30 (09) ◽  
pp. 1650046 ◽  
Author(s):  
S. Zhang ◽  
J. Yin ◽  
H. W. Zhang ◽  
B. S. Chen
Keyword(s):  
Optical Devices ◽  
Two Dimensional ◽  
Regular Pattern ◽  
Multi Objective Optimization ◽  
New Materials ◽  
Optomechanical Systems ◽  
Multi Objective ◽  
Design And Synthesis ◽  
Multi Level ◽  
Photonic Band

Phoxonic crystal (PXC) is a promising artificial periodic material for optomechanical systems and acousto-optical devices. The multi-objective topology optimization of dual phononic and photonic max relative bandgaps in a kind of two-dimensional (2D) PXC is investigated to find the regular pattern of topological configurations. In order to improve the efficiency, a multi-level substructure scheme is proposed to analyze phononic and photonic band structures, which is stable, efficient and less memory-consuming. The efficient and reliable numerical algorithm provides a powerful tool to optimize and design crystal devices. The results show that with the reduction of the relative phononic bandgap (PTBG), the central dielectric scatterer becomes smaller and the dielectric veins of cross-connections between different dielectric scatterers turn into the horizontal and vertical shape gradually. These characteristics can be of great value to the design and synthesis of new materials with different topological configurations for applications of the PXC.

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