Gravitational Search Algorithm and Its Variants

Siddique, Nazmul; Adeli, Hojjat

doi:10.1142/s0218001416390018

Cited by 57 publications

(31 citation statements)

References 78 publications

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“…For instance, in the single-solution category, some of them are inspired by nature (Siddique & Adeli, 2015b), for example, Water Drop Algorithm (Siddique & Adeli, 2014b) and Bacteria-Foraging Algorithm (J. Wang, Zhong, Adeli, Wang, & Liu, 2018), and some of them are inspired by physics (Siddique & Adeli, 2016b), for example, Spiral Dynamics Algorithm (Siddique & Adeli, 2014a) and Gravitational Search Algorithm (Siddique & Adeli, 2016a). Here, we employ the Simulated Annealing (SA) algorithm from the single-solution category inspired by physics.…”

Section: +1mentioning

confidence: 99%

Simulation‐based dynamic traffic assignment: Meta‐heuristic solution methods with parallel computing

Ameli

Lebacque

Leclercq

2020

Computer aided Civil Eng

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The aim of this study is to solve the large‐scale dynamic traffic assignment (DTA) model using a simulation‐based framework, which is computationally a challenging problem. Many studies have been performed on developing an efficient algorithm to solve DTA. Most of the existing algorithms are based on path‐swapping descent direction methods. From the computational standpoint, the main drawback of these methods is that they cannot be parallelized. This is because the existing algorithms need to know the results of the last iteration to determine the next best path flow for the next iteration. Thus, their performance depends on the single initial or intermediate solution, which means they exploit a solution that satisfies the equilibrium conditions more than explore the solution space for the optimal solution. More specifically, the goal of this study is to overcome the drawbacks of serial algorithms by using meta‐heuristic algorithms known to be parallelizable and that have never been applied to the simulation‐based DTA problem. This study proposes two new solution methods: a new extension of the simulated annealing and an adapted genetic algorithm. With parallel simulation, the algorithm runs more simulations in comparison with existing methods, but the algorithm explores the solution space better and therefore obtains better solutions in terms of closeness to the optimal solution and computation time compared to classical methods.

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Section: +1mentioning

confidence: 99%

Simulation‐based dynamic traffic assignment: Meta‐heuristic solution methods with parallel computing

Ameli

Lebacque

Leclercq

2020

Computer aided Civil Eng

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“…In the real Universe, p = 2. In the gravitational search algorithm (Siddique & Adeli, ), p = 2. But in AP, the value of the parameter p ∈ [−5.0, 5.0] can be chosen by the user.…”

Section: Artificial Physics Optimizationmentioning

confidence: 99%

Physics‐based search and optimization: Inspirations from nature

Siddique

Adeli

2016

Expert Systems

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“…Algorithms be-longing to the last category are usually inspired by nature. Some recently proposed examples include inspiration by music [41,40], physics [43,42,44], swarm behavior [34,37,36]. Artificial Intelligence is often integrated within robot controllers [45,28] and combined to neural systems for Machine Intelligence [19,2,13].…”

Section: Introductionmentioning

confidence: 99%

Geometry based three-dimensional image processing method for electronic cluster eye

Zhang

Zhu

et al. 2018

ICA

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In recent years, much attention has been paid to the electronic cluster eye (eCley), a new type of artificial compound eyes, because of its small size, wide field of view (FOV) and sensitivity to motion objects. An eCley is composed of a certain number of optical channels organized as an array. Each optical channel spans a small and fixed field of view (FOV). To obtain a complete image with a full FOV, the images from all the optical channels are required to be fused together. The parallax from unparallel neighboring optical channels in eCley may lead to reconstructed image blurring and incorrectly estimated depth. To solve this problem, this paper proposes a geometry based three-dimensional image processing method (G3D) for eCley to obtain a complete focused image and dense depth map. In G3D, we derive the geometry relationship of optical channels in eCley to obtain the mathematical relation between the parallax and depth among unparallel neighboring optical channels. Based on the geometry relationship, all of the optical channels are used to estimate the depth map and reconstruct a focused image. Subsequently, by using an edge-aware interpolation method, we can further gain a sharply focused image and a depth map. The effectiveness of the proposed method is verified by the experimental results.

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Gravitational Search Algorithm and Its Variants

Cited by 57 publications

References 78 publications

Simulation‐based dynamic traffic assignment: Meta‐heuristic solution methods with parallel computing

Simulation‐based dynamic traffic assignment: Meta‐heuristic solution methods with parallel computing

Physics‐based search and optimization: Inspirations from nature

Geometry based three-dimensional image processing method for electronic cluster eye

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