Chaos embedded opposition based learning for gravitational search algorithm

Joshi, Susheel Kumar

doi:10.1007/s10489-022-03786-9

Cited by 9 publications

(7 citation statements)

References 64 publications

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“…where M aj and M pi represent the active gravitational mass of particle i and passive gravitational mass of particle j, respectively, R is the distance between masses, and M ii represents the inertia mass of particle i. "G(t) is the gravitational constant that decreases iteratively" [178]:…”

Section: Gravitation Search Algorithm (Gsa)mentioning

confidence: 99%

“…The mass j acting on mass i by mass j is the equation

giving the gravitational force and the gravitational acceleration

caused by it ( 28 ) [ 177 ]:

where

and

represent the active gravitational mass of particle i and passive gravitational mass of particle j , respectively, R is the distance between masses, and

represents the inertia mass of particle i . “G(t) is the gravitational constant that decreases iteratively” [ 178 ]:

…”

Section: Heuristic Approachmentioning

confidence: 99%

“…

and

are constant parameters that affect the performance of the algorithm. As for the tuning of the mentioned parameters, many GSA variants have been developed [ 178 ].…”

Section: Heuristic Approachmentioning

confidence: 99%

See 2 more Smart Citations

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

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Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance algorithms play a key role in robotics and autonomous vehicles. These algorithms enable robots to navigate their environment efficiently, minimizing the risk of collisions and safely avoiding obstacles. This article provides an overview of key obstacle avoidance algorithms, including classic techniques such as the Bug algorithm and Dijkstra’s algorithm, and newer developments like genetic algorithms and approaches based on neural networks. It analyzes in detail the advantages, limitations, and application areas of these algorithms and highlights current research directions in obstacle avoidance robotics. This article aims to provide comprehensive insight into the current state and prospects of obstacle avoidance algorithms in robotics applications. It also mentions the use of predictive methods and deep learning strategies.

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Section: Gravitation Search Algorithm (Gsa)mentioning

confidence: 99%

“…The mass j acting on mass i by mass j is the equation

giving the gravitational force and the gravitational acceleration

caused by it ( 28 ) [ 177 ]:

where

and

represent the active gravitational mass of particle i and passive gravitational mass of particle j , respectively, R is the distance between masses, and

represents the inertia mass of particle i . “G(t) is the gravitational constant that decreases iteratively” [ 178 ]:

…”

Section: Heuristic Approachmentioning

confidence: 99%

See 1 more Smart Citation

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

View full text Add to dashboard Cite

show abstract

“…OBL was utilized, too, by Vermaa et al 11 to enhance the convergence of the Firefly technique (FA). Joshi 12 used chaos‐OBL into the standard Gravitational search method (GSA) to provide a diversified search area. Numerous studies have employed the chaos opposition based learning algorithm (C‐OBL) 10 to fortify various optimization methods in the literature.…”

Section: Motivationsmentioning

confidence: 99%

A chaos opposition‐based dwarf mongoose approach for workflow scheduling in cloud

Talha

Bouayad

Malki

2023

Trans Emerging Tel Tech

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Cloud computing (CC) systems are a form of public infrastructure that has been in use since its beginnings. In such technologies, clients can access current services according to their requirements without knowing where the service is hosted or how it is supplied, and only pay for the services that they really consume. The CC system faces several challenges. Due to the large range of clients and services offered by this platform, it can be concluded that the scheduling problem and resource usage are its primary issues. In order to successfully balance the three main qualities of service (QoS) criteria: time, cost, and resource usage, researchers were inspired to improve the workflow scheduling (WFS) methods in cloud. Since the randomness of the initial population and the inadequate exploration/exploitation capacity, which has an impact on the quality of the solutions, traditional intelligent optimization algorithms have a poor convergence rate when it comes to resource scheduling. In this research, we suggested a hybridization method combining the Dwarf Mongoose algorithm (DWO) and Chaos opposition based learning algorithm called CO‐DWO in an attempt to develop a more effective optimization algorithm for workflow scheduling issue. The CO‐DWO can be much more advantageous in optimization with a better convergence rate in comparison with other literature techniques.

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“…Chaos has been applied to many engineering fields, such as communications, signal processing, search algorithm, highperformance reservoir computing, and video watermarking and etc. [8][9][10][11][12]. For example, mathematical symmetry (which means that one shape looks exactly like another when moved, rotated, or flipped.)…”

Section: Introductionmentioning

confidence: 99%

Modification of Intertwining Logistic Map and a Novel Pseudo Random Number Generator

Zhao,

2024

Symmetry

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Chaotic maps have been widely studied in the field of cryptography for their complex dynamics. However, chaos-based cryptosystems have not been widely used in practice. One important reason is that the following requirements of practical engineering applications are not taken into account: computational complexity and difficulty of hardware implementation. In this paper, based on the demand for information security applications, we modify the local structure of the three-dimensional Intertwining Logistic chaotic map to improve the efficiency of software calculation and reduce the cost of hardware implementation while maintaining the complex dynamic behavior of the original map. To achieve the goal by reducing the number of floating point operations, we design a mechanism that can be decomposed into two processes. One process is that the input parameters value of the original system is fixed to 2k by Scale index analysis. The other process is that the transcendental function of the original system is replaced by a nonlinear polynomial. We named the new map as “Simple intertwining logistic”. The basic chaotic dynamic behavior of the new system for controlling parameter is qualitatively analyzed by bifurcation diagram and Lyapunov exponent; the non-periodicity of the sequence generated by the new system is quantitatively evaluated by using Scale index technique based on continuous wavelet change. Fuzzy entropy (FuzzyEn) is used to evaluate the randomness of the new system in different finite precision digital systems. The analysis and evaluation results show that the optimized map could achieve the designed target. Then, a novel scheme for generating pseudo-random numbers is proposed based on new map. To ensure its usability in cryptographic applications, a series of analysis are carried out. They mainly include key space analysis, recurrence plots analysis, correlation analysis, information entropy, statistical complexity measure, and performance speed. The statistical properties of the proposed pseudo random number generator (PRNG) are tested with NIST SP800-22 and DIEHARD. The obtained results of analyzing and statistical software testing shows that, the proposed PRNG passed all these tests and have good randomness. In particular, the speed of generating random numbers is extremely rapid compared with existing chaotic PRNGs. Compared to the original chaotic map (using the same scheme of random number generation), the speed is increased by 1.5 times. Thus, the proposed PRNG can be used in the information security.

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Chaos embedded opposition based learning for gravitational search algorithm

Cited by 9 publications

References 64 publications

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

A chaos opposition‐based dwarf mongoose approach for workflow scheduling in cloud

Modification of Intertwining Logistic Map and a Novel Pseudo Random Number Generator

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