Ensemble Differential Evolution with Simulation-Based Hybridization and Self-Adaptation for Inventory Management Under Uncertainty DOI Creative Commons
Sarit Maitra, Vivek Mishra,

Sukanya Kundu

et al.

arXiv (Cornell University), Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

This study proposes an Ensemble Differential Evolution with Simula-tion-Based Hybridization and Self-Adaptation (EDESH-SA) approach for inven-tory management (IM) under uncertainty. In this study, DE multiple runs is combined a simulation-based hybridization method that includes self-adaptive mechanism dynamically alters mutation crossover rates based on the success or failure of each iteration. Due to its adaptability, algorithm able handle complexity uncertainty present in IM. Utilizing Monte Carlo Simulation (MCS), continuous review (CR) inventory strategy ex-amined while accounting stochasticity various demand scenarios. enables realistic assessment proposed algo-rithm's applicability resolving challenges faced by IM practical settings. The empirical findings demonstrate potential im-prove financial performance optimize large search spaces. makes use testing Ackley function Sensitivity Analysis Perturbations investigate how changes variables affect objective value. analysis provides valuable insights into behavior robustness algorithm.

Language: Английский

RNN-LSTM: From applications to modeling techniques and beyond—Systematic review DOI Creative Commons
Safwan Mahmood Al-Selwi, Mohd Fadzil Hassan, Said Jadid Abdulkadir

et al.

Journal of King Saud University - Computer and Information Sciences, Journal Year: 2024, Volume and Issue: 36(5), P. 102068 - 102068

Published: May 21, 2024

Long Short-Term Memory (LSTM) is a popular Recurrent Neural Network (RNN) algorithm known for its ability to effectively analyze and process sequential data with long-term dependencies. Despite popularity, the challenge of initializing optimizing RNN-LSTM models persists, often hindering their performance accuracy. This study presents systematic literature review (SLR) using an in-depth four-step approach based on PRISMA methodology, incorporating peer-reviewed articles spanning 2018-2023. It aims address how weight initialization optimization techniques can bolster performance. SLR offers detailed overview across various applications domains, stands out by comprehensively analyzing modeling techniques, datasets, evaluation metrics, programming languages associated networks. The findings this provide roadmap researchers practitioners enhance networks achieve superior results.

Language: Английский

Citations

75
A Literature Review and Critical Analysis of Metaheuristics Recently Developed DOI Creative Commons
Luis Velasco, Héctor Guerrero, Antonio Hospitaler

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 31(1), P. 125 - 146

Published: July 22, 2023

Abstract Metaheuristic algorithms have applicability in various fields where it is necessary to solve optimization problems. It has been a common practice this field for several years propose new that take inspiration from natural and physical processes. The exponential increase of controversial issue researchers criticized. However, their efforts point out multiple issues involved these practices insufficient since the number existing metaheuristics continues yearly. To know current state problem, paper analyzes sample 111 recent studies so-called new, hybrid, or improved are proposed. Throughout document, topics reviewed will be addressed general perspective specific aspects. Among study’s findings, observed only 43% analyzed papers make some mention No Free Lunch (NFL) theorem, being significant result ignored by most presented. Of studies, 65% present an version established algorithm, which reveals trend no longer based on analogies. Additionally, compilation solutions found engineering problems commonly used verify performance state-of-the-art demonstrate with low level innovation can erroneously considered as frameworks years, known Black Widow Optimization Coral Reef analyzed. study its components they do not any innovation. Instead, just deficient mixtures different evolutionary operators. This applies extension recently proposed versions.

Language: Английский

Citations

50
Design of Runge-Kutta optimization for fractional input nonlinear autoregressive exogenous system identification with key-term separation DOI
Taimoor Ali Khan, Naveed Ishtiaq Chaudhary, Zeshan Aslam Khan

et al.

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 182, P. 114723 - 114723

Published: March 20, 2024

Language: Английский

Citations

15
A novel hippo swarm optimization: for solving high-dimensional problems and engineering design problems DOI Creative Commons
Guoyuan Zhou,

Jiaxuan Du,

Jia Guo

et al.

Journal of Computational Design and Engineering, Journal Year: 2024, Volume and Issue: 11(3), P. 12 - 42

Published: April 10, 2024

Abstract In recent years, scholars have developed and enhanced optimization algorithms to tackle high-dimensional engineering challenges. The primary challenge of lies in striking a balance between exploring wide search space focusing on specific regions. Meanwhile, design problems are intricate come with various constraints. This research introduces novel approach called Hippo Swarm Optimization (HSO), inspired by the behavior hippos, designed address real-world HSO encompasses four distinct strategies based hippos different scenarios: starvation search, alpha margination, competition. To assess effectiveness HSO, we conducted experiments using CEC2017 test set, featuring highest dimensional problems, CEC2022 constrained problems. parallel, employed 14 established as control group. experimental outcomes reveal that outperforms well-known algorithms, achieving first average ranking out them CEC2022. Across classical consistently delivers best results. These results substantiate highly effective algorithm for both

Language: Английский

Citations

6
Integrated improved Harris hawks optimization for global and engineering optimization DOI Creative Commons

Chengtian Ouyang,

Liao Chang, Donglin Zhu

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 28, 2024

Abstract The original Harris hawks optimization (HHO) algorithm has the problems of unstable effect and easy to fall into stagnation. However, most improved HHO algorithms can not effectively improve ability jump out local optimum. In this regard, an integrated (IIHHO) is proposed. Firstly, linear transformation escape energy used by relatively simple lacks law prey in actual nature. Therefore, intermittent regulator introduced adjust hawks, which conducive improving search while restoring prey's rest mechanism; Secondly, uncertainty random vector, a more regular vector change mechanism instead, attenuation obtained modifying composite function. Finally, scope Levy flight further clarified, jumping order modify calculation limitations caused fixed step size, Cardano formula function size setting accuracy algorithm. First, performance IIHHO analyzed on Computational Experimental Competition 2013 (CEC 2013) test set compared with seven evolutionary algorithms, convergence value iterative curve better than verifying effectiveness proposed Second, another three state art (SOTA) 2022 2022) set, experiments show that still strong for optimal value. Third, applied two different engineering experiments. results minimum cost prove certain advantages dealing problem space. All these demonstrate promising numeric applications.

Language: Английский

Citations

4
Improved snake optimizer based on forced switching mechanism and variable spiral search for practical applications problems DOI
Yan‐Feng Wang, Baohua Xin, Zicheng Wang

et al.

Soft Computing, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Language: Английский

Citations

0
An Introduction to Advanced Optimization and Nature-Inspired Computing Solutions in Engineering Applications DOI
Diego Gabriel Rossit, Carlos Torres-Aguilar, Adrián Toncovich

et al.

Springer tracts in nature-inspired computing, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 12

Published: Jan. 1, 2025

Language: Английский

Citations

0
A Novel Technique for Optimization of Artificial Neural Network Using Ensemble of Chimp, Harris Hawks and Manta Ray Foraging Optimization Algorithms for Enhancing Software Maintainability Prediction DOI

Varun Goel -,

Arvinder Kaur

Arabian Journal for Science and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Language: Английский

Citations

0
Multi-objective task scheduling algorithm for load balancing in cloud computing based on improved Harris hawks optimization DOI
Farouk A. Emara, Ahmed A. A. Gad-Elrab, Ahmed Sobhi

et al.

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(6)

Published: April 28, 2025

Language: Английский

Citations

0
Multi-strategy improved seagull optimization algorithm and its application in practical engineering DOI
Peng Chen, Huilin Li, Feng He

et al.

Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 39

Published: July 24, 2024

Metaheuristic algorithms play a crucial role in engineering optimization, as they can find the optimal parameter configuration systems. This article proposes multi-strategy improved seagull optimization algorithm (OPSOA) to solve application problems. Aiming problems of slow search speed and low convergence accuracy standard (SOA), four strategies, including Lévy flight Cauchy mutation, were introduced improve its performance. Comparison shows that OPSOA incomplete are better than SOA, indicating each improvement is effective. By testing benchmark functions CEC 2017 2022, it shown has strong ability solution superior other terms speed. The this practical proves significant advantages solving complex

Language: Английский

Citations

3