Slime mould algorithm: A comprehensive survey of its variants and applications

FS Gharehchopogh, A Ucan, T Ibrikci, B Arasteh… - … Methods in Engineering, 2023 - Springer
Meta-heuristic algorithms have a high position among academic researchers in various
fields, such as science and engineering, in solving optimization problems. These algorithms …

Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent

RZ Homod, HI Mohammed, A Abderrahmane, OA Alawi… - Applied Energy, 2023 - Elsevier
The intelligent buildings provided various incentives to get highly inefficient energy-saving
caused by the non-stationary building environments. In the presence of such dynamic …

Deep clustering of cooperative multi-agent reinforcement learning to optimize multi chiller HVAC systems for smart buildings energy management

RZ Homod, ZM Yaseen, AK Hussein… - Journal of Building …, 2023 - Elsevier
Chillers are responsible for almost half of the total energy demand in buildings. Hence, the
obligation of control systems of multi-chiller due to changes indoor environments is one of …

Advances in Slime Mould Algorithm: A Comprehensive Survey

Y Wei, Z Othman, KM Daud, Q Luo, Y Zhou - Biomimetics, 2024 - mdpi.com
The slime mould algorithm (SMA) is a new swarm intelligence algorithm inspired by the
oscillatory behavior of slime moulds during foraging. Numerous researchers have widely …

An enhanced slime mould algorithm based on adaptive grou** technique for global optimization

L Deng, S Liu - Expert Systems with Applications, 2023 - Elsevier
When solving global optimization problems by metaheuristic algorithms (MAs), an important
issue is how to keep a balance between convergence and diversity. This article develops an …

Deep clustering of reinforcement learning based on the bang-bang principle to optimize the energy in multi-boiler for intelligent buildings

RZ Homod, BS Munahi, HI Mohammed, MAA Albadr… - Applied Energy, 2024 - Elsevier
The bang-bang relays of the multiple-boiler system (MBS) control, are characterized by
complex limiter saturation functions and classified as fixed parameters. Their action signals …

Improved slime mould algorithm based on hybrid strategy optimization of Cauchy mutation and simulated annealing

X Zhang, Q Liu, X Bai - PLoS One, 2023 - journals.plos.org
In this article, an improved slime mould algorithm (SMA-CSA) is proposed for solving global
optimization and the capacitated vehicle routing problem (CVRP). This improvement is …

A novel approach for optimal energy resources mixing in nuclear-renewable microgrids using probabilistic energy modelling method

MR Abdussami, A Ahmed, TH Sakib - Energy Conversion and Management, 2023 - Elsevier
Zero-carbon energy infrastructure design has become one of the most consequential pivotal
toward sustainable development. This article introduces a novel approach to energy …

Bivariate simulation of river flow using hybrid intelligent models in sub-basins of Lake Urmia, Iran

V Eslamitabar, F Ahmadi, A Sharafati… - Acta Geophysica, 2023 - Springer
In this study, the performance of continuous autoregressive moving average (CARMA),
CARMA-generalized autoregressive conditional heteroscedasticity (CARMA-GARCH) …

Spectral transient-based multiple leakage identification in water pipelines: An efficient hybrid gradient-metaheuristic optimization

A Keramat, I Ahmadianfar, HF Duan, Q Hou - Expert Systems with …, 2023 - Elsevier
In transient-based leak detection (TBLD), the localization of multiple leaks from the
measurement data of a few stations is challenging. Recent studies have made …