Grey Wolf Optimizer, Whale Optimization Algorithm, and Moth Flame Optimization for Optimizing Photonics Crystals

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Author(s)
Mirjalili, SM
Mirjalili, SZ
Khodadadi, N
Snasel, V
Mirjalili, S
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Biswas, Anupam

Kalayci, Can B.

Mirjalili, Seyedali

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2023
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Abstract

In this chapter, three recent swarm intelligence algorithms are used to solve a challenging optimization problem in the field of photonics, including Grey Wolf Optimizer, Whale Optimization Algorithm, and Moth Flame Optimization Algorithm. The problem is to optimize the radii of several rods in a photonics crystal to minimize light wave loss when there is a bend corner. This problem is first presented and formulated in details. It is discussed that due to the use of complex simulations, analytics equations are ill-defined for this problem thereby justifying the use of black-box optimization algorithms. The above-mentioned algorithms are then employed to estimate the global optimal for this problem by finding the optimal values for its structural parameters. The results show that the GWO algorithm provides the best results. The chapter also considers a convergence analysis of all algorithms that led to interesting insights about the process of solution improved during the course of optimization. It is observed that GWO shows constant improvement while others tend to show steady and slow improvement.

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Advances in Swarm Intelligence: Variations and Adaptations for Optimization Problems

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1054

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Artificial intelligence

Nanotechnology

Control engineering, mechatronics and robotics

Machine learning

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Mirjalili, SM; Mirjalili, SZ; Khodadadi, N; Snasel, V; Mirjalili, S, Grey Wolf Optimizer, Whale Optimization Algorithm, and Moth Flame Optimization for Optimizing Photonics Crystals, Advances in Swarm Intelligence: Variations and Adaptations for Optimization Problems, 2023, 1054, pp. 169-179

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