Hybrid slime mould algorithm with adaptive guided differential evolution algorithm for combinatorial and global optimization problems

Expert Systems with Applications, Journal Year: 2021, Volume and Issue: 174, P. 114689 - 114689

Published: Feb. 15, 2021

Language: Английский

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Slime mould algorithm: a comprehensive review of recent variants and applications

International Journal of Systems Science, Journal Year: 2022, Volume and Issue: 54(1), P. 204 - 235

Published: Dec. 16, 2022

Slime Mould Algorithm (SMA) has recently received much attention from researchers because of its simple structure, excellent optimisation capabilities, and acceptable convergence in dealing with various types complex real-world problems. this study aims to retrieve, identify, summarise analyse critical studies related SMA development. Based on this, 98 SMA-related the Web Science were retrieved, selected, identified. The two main review vectors advanced versions SMAs application domains. First, we counted analysed SMAs, summarised, classified, discussed their improvement methods directions. Secondly, sort out domains role, development status, shortcomings each domain. A survey based existing literature shows that clearly outperform some established metaheuristics terms speed accuracy handling benchmark problems solving multiple realistic optimization This not only suggests possible future directions field but, due inclusion graphical tabular comparisons properties, also provides a comprehensive source information about SAMs scope adaptation for

Language: Английский

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Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 30(4), P. 2683 - 2723

Published: Jan. 12, 2023

Language: Английский

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Predicting the energy consumption in buildings using the optimized support vector regression model

Energy, Journal Year: 2023, Volume and Issue: 273, P. 127188 - 127188

Published: March 13, 2023

Language: Английский

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Application of artificial intelligence in digital twin models for stormwater infrastructure systems in smart cities

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 61, P. 102485 - 102485

Published: March 26, 2024

Language: Английский

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Multi-Objective Optimal Power Flow Problems Based on Slime Mould Algorithm

Sustainability, Journal Year: 2021, Volume and Issue: 13(13), P. 7448 - 7448

Published: July 2, 2021

Solving the optimal power flow problems (OPF) is an important step in optimally dispatching generation with considered objective functions. A single-objective function inadequate for modern systems, required high-performance generation, so problem becomes multi-objective (MOOPF). Although MOOPF has been widely solved by many algorithms, new solutions are still to obtain better performance of generation. Slime mould algorithm (SMA) a recently proposed metaheuristic that applied solve several optimization different fields, except problem, while it outperforms various algorithms. Thus, this paper proposes solving based on SMA considering cost, emission, and transmission line loss as part functions system. The IEEE 30-, 57-, 118-bus systems used investigate problems. values generated compared those other algorithms literature. simulation results show provides than literature, Pareto fronts presenting can be efficiently obtained.

Language: Английский

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A novel version of slime mould algorithm for global optimization and real world engineering problems

Mathematics and Computers in Simulation, Journal Year: 2022, Volume and Issue: 198, P. 253 - 288

Published: March 10, 2022

Language: Английский

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EOSMA: An Equilibrium Optimizer Slime Mould Algorithm for Engineering Design Problems

Arabian Journal for Science and Engineering, Journal Year: 2022, Volume and Issue: 47(8), P. 10115 - 10146

Published: Jan. 6, 2022

Language: Английский

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Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review

Evolving Systems, Journal Year: 2022, Volume and Issue: 13(6), P. 889 - 945

Published: Feb. 21, 2022

Language: Английский

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DTSMA: Dominant Swarm with Adaptive T-distribution Mutation-based Slime Mould Algorithm

Mathematical Biosciences & Engineering, Journal Year: 2022, Volume and Issue: 19(3), P. 2240 - 2285

Published: Jan. 1, 2022

<abstract> <p>The slime mould algorithm (SMA) is a metaheuristic recently proposed, which inspired by the oscillations of mould. Similar to other algorithms, SMA also has some disadvantages such as insufficient balance between exploration and exploitation, easy fall into local optimum. This paper, an improved based on dominant swarm with adaptive t-distribution mutation (DTSMA) proposed. In DTSMA, used SMA's convergence speed, balances enhanced exploitation ability. addition, new mechanism hybridized increase diversity populations. The performances DTSMA are verified CEC2019 functions eight engineering design problems. results show that for functions, best; problems, obtains better than many algorithms in literature when constraints satisfied. Furthermore, solve inverse kinematics problem 7-DOF robot manipulator. overall strong optimization Therefore, promising global problems.</p> </abstract>

Language: Английский

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