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Book ChapterDOI

Optimization of Railway Bogie Snubber Spring with Grasshopper Algorithm

TL;DR: In this article, the design of snubber spring is optimized by using grasshopper optimization algorithm, which simulates the behaviour of the grasshoppers in nature and models that mathematically for solving optimization problems.
Abstract: Swarm intelligence is a branch which deals in research that models the population of interacting agents or swarms that are self-organizing in nature. Grasshopper optimization algorithm is a modern algorithm for optimization which is inspired from the swarm-based nature. This algorithm simulates the behaviour of the grasshopper in nature and models that mathematically for solving optimization problems. Grasshopper optimization algorithm is used for the optimization of mechanical components and systems. Snubber spring is a kind of helical spring which is a part of suspension system in railway bogie. In this work, the design of snubber spring is optimized by using grasshopper optimization algorithm. The suspension system of railway bogie consists of inner spring, outer spring, and snubber spring. Optimization is done for the weight minimization of snubber spring. Wire diameter, number of active turns and mean coil diameter are the design parameters for the optimization. These parameters are optimized by using grasshopper optimization algorithm according to bounds, loading, and boundary conditions. The optimized parameters are validated experimentally and also by using a software. The spring is modelled in CATIA V5 and analyzed in ANSYS 17.0. The comparison of results is done and is validated with results experimentally in which the spring is tested on universal testing machine for compression test.
Citations
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Journal ArticleDOI
TL;DR: A comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others is presented in this article.
Abstract: Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired by the foraging and swarming behavior of grasshoppers in nature. The GOA algorithm has been successfully applied to solve various optimization problems in several domains and demonstrated its merits in the literature. This paper proposes a comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others. It provides the GOA variants, including multi-objective and hybrid variants. It also discusses the main applications of GOA in various fields such as scheduling, economic dispatch, feature selection, load frequency control, distributed generation, wind energy system, and other engineering problems. Finally, the paper provides some possible future research directions in this area.

98 citations

Journal ArticleDOI
11 Aug 2021
TL;DR: In this paper, the Bat algorithm was used to predict the optimal surface value (Ra) and process parameters for EN8 steel turning, which showed that the feed rate is the most important factor affecting the surface roughness.
Abstract: Due to its high precision, productivity, and surface quality, computer numerical control turning (CNC) is a desirable processing tool in the traditional processing area. CNC machining procedures have a huge number of process parameters, making it challenging to find the best combination of parameters for increased accuracy. In this research work, the Taguchi method and ANOVA were used to study the effects of CNC machining parameters in EN8 steel turning: Surface roughness (Ra) value of component affected due to cutting speed, depth of cut and feed rate. Three-level three-parameter experimental design, using Minitab 17 software using L9 orthogonal array, using coated carbide insert cutting tools, using signal-to-noise ratio (S/N) to study the performance characteristics of EN8 steel turning. In this study, statistical approaches such as the signal-to-noise ratio (S/N ratio) and analysis of variance (ANOVA) were used to explore the effects of cutting speed, depth of cut, and feed rate on surface roughness. Nature-inspired algorithms play a vital role in solving real life. In this study, the bat algorithm can be used to predict the optimal surface value (Ra) and process parameters. Verify the results by conducting confirmation experiments. The current research shows that the feed rate is the most important factor affecting the surface roughness (Ra) of EN8 steel turning.

2 citations

Journal ArticleDOI
17 Apr 2022-Technium
TL;DR: The benefits of the GOA algorithm have been effective in answering global unrestricted and restricted optimization issues, easy development, high accuracy, and obtaining a good solution, however, the disadvantages are simple to fall into local optimum and slow convergence speed.
Abstract: The metaheuristic optimization algorithm is used to explain a large region solution space. One of these algorithms is a grasshopper which divides the search process into exploitation and exploration. This article focuses on research efforts directed at gaining a clear understanding of the behavior of grasshoppers and it is using optimization algorithms. It is concluded that the benefits have been effective in answering global unrestricted and restricted optimization issues, easy development, high accuracy, and obtaining a good solution. However, the disadvantages of the GOA algorithm are simple to fall into local optimum and slow convergence speed.

2 citations

Book ChapterDOI
01 Jan 2022
TL;DR: In this article , an attempt is made to proposed mathematical model to understand the nature of sliding friction and optimized with theoretical bounds using Gorilla Troops Optimizer, values of sliding frictional force obtained through optimizer found to be significant.
Abstract: The root canal treatment is a therapeutic intervention that aids in the recovery of a decaying and sore tooth. Root canal therapy is used to preserve diseased or partially destroyed teeth. Obturation is the dental term for root canal therapy used to form a fluid-tight barrier between the canal walls and the filled soften gutta-percha. After the heat application an instrument called a plugger portion vertical condensed soften gutta-percha to form relatively densely compressed mass within the canal of the tooth. This condensation forces gutta-percha to slide inside the cavity generating the sliding fiction between canal walls and gutta-percha. In this article, an attempt is made to proposed mathematical model to understand the nature of sliding friction and optimized with theoretical bounds using Gorilla Troops Optimizer. On comparison of results, values of sliding frictional force obtained through optimizer found to be significant.
References
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Journal ArticleDOI
13 May 1983-Science
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Abstract: There is a deep and useful connection between statistical mechanics (the behavior of systems with many degrees of freedom in thermal equilibrium at a finite temperature) and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters). A detailed analogy with annealing in solids provides a framework for optimization of the properties of very large and complex systems. This connection to statistical mechanics exposes new information and provides an unfamiliar perspective on traditional optimization problems and methods.

41,772 citations

Journal ArticleDOI
Rainer Storn1, Kenneth Price
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Abstract: A new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented. By means of an extensive testbed it is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods. The new method requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.

24,053 citations

Book
01 Jan 2002

17,039 citations

Proceedings ArticleDOI
04 Oct 1995
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Abstract: The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm. Benchmark testing of both paradigms is described, and applications, including neural network training and robot task learning, are proposed. Relationships between particle swarm optimization and both artificial life and evolutionary computation are reviewed.

14,477 citations

Journal ArticleDOI
TL;DR: The elements of staged search and structured move sets are characterized, which bear on the issue of finiteness, and new dynamic strategies for managing tabu lists are introduced, allowing fuller exploitation of underlying evaluation functions.
Abstract: This is the second half of a two part series devoted to the tabu search metastrategy for optimization problems. Part I introduced the fundamental ideas of tabu search as an approach for guiding other heuristics to overcome the limitations of local optimality, both in a deterministic and a probabilistic framework. Part I also reported successful applications from a wide range of settings, in which tabu search frequently made it possible to obtain higher quality solutions than previously obtained with competing strategies, generally with less computational effort. Part II, in this issue, examines refinements and more advanced aspects of tabu search. Following a brief review of notation, Part II introduces new dynamic strategies for managing tabu lists, allowing fuller exploitation of underlying evaluation functions. In turn, the elements of staged search and structured move sets are characterized, which bear on the issue of finiteness. Three ways of applying tabu search to the solution of integer programmin...

5,883 citations