Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería / International Journal of Numerical Methods for Calculation and Design in Engineering

RIMNI - An International Journal of Numerical Methods for Calculation and Design in Engineering (Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería) is a peer-reviewed Open Access journal, founded in 1985. RIMNI publishes articles written in Spanish and English. The journal's scope includes Computational and Numerical Models of Engineering Problems, Development and Application of Numerical Methods, Advances in Software, Computer Design Innovations, Soft Computing, Machine Learning, Artificial Intelligence, etc. RIMNI is an essential ... show more

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Comparison with Different Bayesian and non-Bayesian Estimation Techniques for the Compound Rayleigh Exponential Distribution with Actuarial Measures and Applications
I. Alkhairy, H. Alsuhabi

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. Online First, 75

Abstract
Many lifetime analysis, such as engineering, biology, survival, actuarial and medical sciences, heavily rely on the two-parameter compound Rayleigh exponential distribution, which is well-known in statistical theory. Because of their ability to successfully handle small sample sizes and involve prior knowledge, Bayesian techniques are crucial for estimating the parameters of the compound Rayleigh exponential distribution. This study presents the estimation of the compound Rayleigh exponential distribution unknown parameters using Bayesian and non-Bayesian estimation techniques, including maximum likelihood estimation, maximum product spacing, least square estimator, weighted least square estimator, Cramer-Von-Mise estimator, Anderson-Darling estimator, and Bayesian techniques with informative and non-informative priors based on different loss functions. Additionally, we used several methods to obtain the confidence intervals for the unknown parameters, such as the approximate and Bootstrap methods. The effectiveness of these estimators is evaluated through a Monte Carlo simulation study. Furthermore, we are committed to investigating three widely recognized risk metrics: the value at risk, the tail value at risk, and the tail variance premium. These findings are helpful for actuarial risk researchers who depend on risk measurement fitting when evaluating Bayesian tools for effectively modeling actuarial sciences. Finally, different applications taken from several areas are examined to illustrate the practical usefulness of the compound Rayleigh exponential distribution. Using various model selection criteria, the introduced model is contrasted with that of several well-known distributions. Our empirical findings indicate that the suggested model has superior goodness-of-fit to the other models examined.
Abstract
Many lifetime analysis, such as engineering, biology, survival, actuarial and medical sciences, heavily rely on the two-parameter compound Rayleigh exponential distribution, [...]
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Freshwater Snail Optimizer: A Bio-Inspired Optimizer for Engineering Design Problems
G. Liu, J. Pan, S. Chu, R. Wang, B. Yang, Y. Yu, S. Mirjalili

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. Online First, 85

Abstract
As the scale and nonlinearity of optimization problems continue to increase, traditional deterministic solution strategies are becoming increasingly flawed in the face of the exponential growth of search space dimensions and multimodal objective functions. Metaheuristic algorithms, with their probability-driven global search capabilities and local development capabilities, have gradually become an essential tool for solving complex optimization tasks. We propose a Freshwater Snail Optimizer (FSO), inspired by the social behavior of water snails in terms of movement and collision, as a metaheuristic algorithm. FSO combines the floating of water snails’ air chambers, movement in the water, and population collisions and divides them into groups during initialization to balance exploration and development, achieving gratifying optimization results, especially in high-dimensional problems. We utilized CEC 2017 and CEC 2022 to qualitatively analyze FSO in various problems, and employed the Friedman test and Wilcoxon rank sum test for statistical testing. Experimental results show that our proposed FSO achieved 32 first-place results on 41 problems compared with 9 classic algorithms, and 27 first-place results when compared with 9 emerging algorithms that appeared in the past two years. FSO has also achieved the first comparison results in six engineering optimizations on multiple occasions, proving that FSO possesses well optimization capabilities and practicality for real-world problems. The source code accompanying this article has been released at:https://github.com/leogalaxy0603/Freshwater-SnailOptimizer(accessed on 12 October 2025).OPEN ACCESS Received: 19/08/2025 Accepted: 13/10/2025
Abstract
As the scale and nonlinearity of optimization problems continue to increase, traditional deterministic solution strategies are becoming increasingly flawed in the face of [...]
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