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Your search keyword '"METAHEURISTIC algorithms"' showing total 2 results
Start Over Descriptor "METAHEURISTIC algorithms" Topic metaheuristic Topic optimization Publisher emerald publishing limited
2 results on '"METAHEURISTIC algorithms"'

1. Crystal structure optimization approach to problem solving in mechanical engineering design.

Author

Talatahari, Babak, Azizi, Mahdi, Talatahari, Siamak, Tolouei, Mohamad, and Sareh, Pooya

Subjects
*CRYSTAL structure, *ENGINEERING design, *MECHANICAL engineering, *MECHANICAL engineers, *METAHEURISTIC algorithms, *PROBLEM solving
Abstract

Purpose: In this paper, the authors aim to examine and comparatively evaluate a recently-developed metaheuristic called crystal structure algorithm (CryStAl) – which is inspired by the symmetries in the internal structure of crystalline solids – in solving engineering mechanics and design problems. Design/methodology/approach: A total number of 20 benchmark mathematical functions are employed as test functions to evaluate the overall performance of the proposed method in handling various functions. Moreover, different classical and modern metaheuristic algorithms are selected from the optimization literature for a comparative evaluation of the performance of the proposed approach. Furthermore, five well-known mechanical design examples are utilized to examine the capability of the proposed method in dealing with challenging optimization problems. Findings: The results of this study indicated that, in most cases, CryStAl produced more accurate outputs when compared to the other metaheuristics examined as competitors. Research limitations/implications: This paper can provide motivation and justification for the application of CryStAl to solve more complex problems in engineering design and mechanics, as well as in other branches of engineering. Originality/value: CryStAl is one of the newest metaheuristic algorithms, the mathematical details of which were recently introduced and published. This is the first time that this algorithm is applied to solving engineering mechanics and design problems. [ABSTRACT FROM AUTHOR]

Published
2022
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2. A simple diversity guided firefly algorithm.

Author

Yu, Shuhao, Su, Shoubao, and Huang, Li

Subjects
*MATHEMATICAL models of population, *LOGISTIC model (Demography), *METAHEURISTIC algorithms, *COMBINATORIAL optimization, *DISCRETE choice models
Abstract

Purpose -- The purpose of this paper is to present a modified firefly algorithm (FA) considering the population diversity to avoid local optimum and improve the algorithm's precision. Design/methodology/approach -- When the population diversity is below the given threshold value, the fireflies' positions update according to the modified equation which can dynamically adjust the fireflies' exploring and exploiting ability. Findings -- A novel metaheuristic algorithm called FA has emerged. It is inspired by the flashing behavior of fireflies. In basic FA, randomly generated solutions will be considered as fireflies, and brightness is associated with the objective function to be optimized. However, during the optimization process, the fireflies become more and more similar and gather into the neighborhood of the best firefly in the population, which may make the algorithm prematurely converged around the local solution. Research limitations/implications -- Due to different dimensions and different ranges, the population diversity is different undoubtedly. And how to determine the diversity threshold value is still required to be further researched. Originality/value -- This paper presents a modified FA which uses a diversity threshold value to guide the algorithm to alternate between exploring and exploiting behavior. Experiments on 17 benchmark functions show that the proposed algorithm can improve the performance of the basic FA. [ABSTRACT FROM AUTHOR]

Published
2015
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