A Spring Search Algorithm Applied to Engineering Optimization Problems

Dehghani, Mohammad; Montazeri, Zeinab; Dhiman, Gaurav; Malik, O.P.; Morales-Menéndez, Rubén; Ramírez-Mendoza, Ricardo A.; Dehghani, Ali; Guerrero, Josep M.; Parra-Arroyo, Lizeth

doi:10.3390/app10186173

Cited by 113 publications

(51 citation statements)

References 84 publications

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“…It has been observed from the results presented in Table 6 that our proposed technique performs better than some existing methods in terms of embedding time. The addition of optimization algorithms [22,[32][33][34][35][36][37][38][39][40][41][42][43] to the proposed approach can positively impact high values of quality metrics (PSNR).…”

Section: Comparison With Existing Methodsmentioning

confidence: 99%

A Robust Image Encrypted Watermarking Technique for Neurodegenerative Disorder Diagnosis and Its Applications

Sharma

Bagga

Sobti

et al. 2021

Computational and Mathematical Methods in Medicine

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The use of Internet technology has led to the availability of different multimedia data in various formats. The unapproved customers misuse multimedia information by conveying them on various web objections to acquire cash deceptively without the first copyright holder’s intervention. Due to the rise in cases of COVID-19, lots of patient information are leaked without their knowledge, so an intelligent technique is required to protect the integrity of patient data by placing an invisible signal known as a watermark on the medical images. In this paper, a new method of watermarking is proposed on both standard and medical images. The paper addresses the use of digital rights management in medical field applications such as embedding the watermark in medical images related to neurodegenerative disorders, lung disorders, and heart issues. The various quality parameters are used to figure out the evaluation of the developed method. In addition, the testing of the watermarking scheme is done by applying various signal processing attacks.

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Section: Comparison With Existing Methodsmentioning

confidence: 99%

A Robust Image Encrypted Watermarking Technique for Neurodegenerative Disorder Diagnosis and Its Applications

Sharma

Bagga

Sobti

et al. 2021

Computational and Mathematical Methods in Medicine

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“…One of these optimizers is the gravitational search (GS), which was formulated by simulating the law of gravitational force between objects [ 22 ]. Simulation of the Hooke and spring displacement laws were applied to designing the spring search algorithm [ 23 ]. In this algorithm, population members correspond to weights connected to each other by different springs.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Two-Stage Algorithm for Solving Optimization Problems

Doumari

Givi

Dehghani

et al. 2021

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Optimization seeks to find inputs for an objective function that result in a maximum or minimum. Optimization methods are divided into exact and approximate (algorithms). Several optimization algorithms imitate natural phenomena, laws of physics, and behavior of living organisms. Optimization based on algorithms is the challenge that underlies machine learning, from logistic regression to training neural networks for artificial intelligence. In this paper, a new algorithm called two-stage optimization (TSO) is proposed. The TSO algorithm updates population members in two steps at each iteration. For this purpose, a group of good population members is selected and then two members of this group are randomly used to update the position of each of them. This update is based on the first selected good member at the first stage, and on the second selected good member at the second stage. We describe the stages of the TSO algorithm and model them mathematically. Performance of the TSO algorithm is evaluated for twenty-three standard objective functions. In order to compare the optimization results of the TSO algorithm, eight other competing algorithms are considered, including genetic, gravitational search, grey wolf, marine predators, particle swarm, teaching-learning-based, tunicate swarm, and whale approaches. The numerical results show that the new algorithm is superior and more competitive in solving optimization problems when compared with other algorithms.

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“…unimodal [53,54], multimodal [31,54], and fixed-dimension multimodal [54] functions (see Appendix A). (4) Implement the present work and the optimization algorithms in the same computational platform.…”

Section: Algorithms Used For Comparisons and Benchmark Test Functionsmentioning

confidence: 99%

DM: Dehghani Method for Modifying Optimization Algorithms

et al. 2020

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In recent decades, many optimization algorithms have been proposed by researchers to solve optimization problems in various branches of science. Optimization algorithms are designed based on various phenomena in nature, the laws of physics, the rules of individual and group games, the behaviors of animals, plants and other living things. Implementation of optimization algorithms on some objective functions has been successful and in others has led to failure. Improving the optimization process and adding modification phases to the optimization algorithms can lead to more acceptable and appropriate solution. In this paper, a new method called Dehghani method (DM) is introduced to improve optimization algorithms. DM effects on the location of the best member of the population using information of population location. In fact, DM shows that all members of a population, even the worst one, can contribute to the development of the population. DM has been mathematically modeled and its effect has been investigated on several optimization algorithms including: genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), teaching-learning-based optimization (TLBO), and grey wolf optimizer (GWO). In order to evaluate the ability of the proposed method to improve the performance of optimization algorithms, the mentioned algorithms have been implemented in both version of original and improved by DM on a set of twenty-three standard objective functions. The simulation results show that the modified optimization algorithms with DM provide more acceptable and competitive performance than the original versions in solving optimization problems.

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A Spring Search Algorithm Applied to Engineering Optimization Problems

Cited by 113 publications

References 84 publications

A Robust Image Encrypted Watermarking Technique for Neurodegenerative Disorder Diagnosis and Its Applications

A Robust Image Encrypted Watermarking Technique for Neurodegenerative Disorder Diagnosis and Its Applications

A New Two-Stage Algorithm for Solving Optimization Problems

DM: Dehghani Method for Modifying Optimization Algorithms

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