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Wireless sensor nodes localiser based on sine-cosine algorithm

IET WIRELESS SENSOR SYSTEMS 2020年第4期10卷 145-153页

作者： Hamouda, Eslam Abohamama, Abdelaziz Said Jouf Univ Dept Comp Sci Sakaka 2014 Saudi Arabia Mansoura Univ Dept Comp Sci Mansoura 35516 Egypt

Wireless sensor networks are an emerging technology deployed in many fields. Knowing the positions of sensor nodes is critical for many applications to perform their tasks. Hence, accurate node localisation in wireless sensor networks is an essential issue. The node localisation problem can be formulated as a multidimensional optimisation problem. In this study, the authors propose a node localisation scheme based on a sine-cosine algorithm. The proposed scheme addresses the flip ambiguity problem, which can badly affect the localisation accuracy of the entire network. The efficacy of the proposed scheme is evaluated through intensive experimentation under different scenarios. The obtained results show the superiority of the proposed scheme against other optimisation algorithms in terms of the localisation accuracy, the number of localised nodes, and the computation time.

关键词： sensor placement optimisation wireless sensor networks wireless sensor networks node localisation problem multidimensional optimisation problem node localisation scheme flip ambiguity problem localisation accuracy optimisation algorithms sine-cosine optimisation algorithm wireless sensor node localiser

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Predicting municipal solid waste using a coupled artificial neural network with archimedes optimisation algorithm and socioeconomic components

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JOURNAL OF CLEANER PRODUCTION 2021年 315卷 128039-128039页

作者： Liang, Guoxi Panahi, Fatemeh Ahmed, Ali Najah Ehteram, Mohammad Band, Shahab S. Elshafie, Ahmed Wenzhou Polytech Dept Informat Technol Wenzhou 325035 Peoples R China Univ Kashan Fac Nat Resources & Earth Sci Kashan Iran Univ Tenaga Nasional UNITEN Inst Energy Infrastruct IEI Coll Engn Dept Civil Engn Selangor 43000 Malaysia Semnan Univ Fac Civil Engn Dept Water Engn & Hydraul Struct Semnan Iran Natl Yunlin Univ Sci & Technol Coll Future Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Univ Malaya UM Fac Engn Dept Civil Engn Kuala Lumpur 50603 Malaysia United Arab Emirates Univ Natl Water & Energy Ctr POB 15551 Al Ain U Arab Emirates

Solid Waste (SW) is one of the critical challenges of urban life. These SWs are considered environmental pollutants that are a threat to ecology and human health. Predicting SW generation is an essential topic for scholars to better manage SWs. This study investigates the application of optimised ANN models for predicting monthly SW generation in Iran using datasets about seven Iranian megacities. The Archimedes optimisation Algorithm (AOA), Sine Cosine Algorithm (SCA), Particle Swarm optimisation (PSO) technique, and Genetic algorithms (GA) were used for training the ANN model. The enhanced gamma test was used to determine the best input combination. AOA and the gamma test were used concurrently to reduce the time needed for choosing the best input combination. Gross domestic product (GDP), population, household size, and numbers of months were the best input combination set. This best input combination was then inputted into the hybrid and standalone ANN models for predicting monthly SW generation. During the final phase, the outputs of ANN-AOA, ANN-SCA, ANNPSO, ANN-GA, and ANN models were used as inputs for an inclusive multiple model (IMM) in order to enhance model accuracy. The IMM model reduced the training phase root mean square error (RMSE) of ANN-AOA, ANNSCA, ANN-PSO, ANN-GA, and ANN models by 55%, 59%, 68%, 72%, and 73%, respectively. Although ANN-AOA provided higher R2 and lower RMSE values than ANN-PSO, ANN-SCA, ANN-GA and ANN models, the IMM model outperformed ANN-AOA, considering that it integrates the advantages of all models used in the current study. The current study also used the fuzzy reasoning concept for modifying ANN model structures. The results indicated that such ANN models' time requirement was lower than those without fuzzy reasoning concept. The general results of the current study indicate that the ANN-AOA and the fuzzy-reasoning based Inclusive Multiple Model have a high ability for predicting different target variables.

关键词： Solid waste Artificial neural network optimisation algorithms Inclusive multiple model

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Multi-Mode Wave Energy Converter Design optimisation Using an Improved Moth Flame optimisation Algorithm

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ENERGIES 2021年第13期14卷 3737页

作者： Neshat, Mehdi Sergiienko, Nataliia Y. Mirjalili, Seyedali Nezhad, Meysam Majidi Piras, Giuseppe Garcia, Davide Astiaso Torrens Univ Australia Ctr Artificial Intelligence Res & Optimisat Brisbane Qld 4006 Australia Univ Adelaide Sch Mech Engn Adelaide SA 5001 Australia Yonsei Univ Yonsei Frontier Lab Seoul 03722 South Korea Sapienza Univ Rome Dept Astronaut Elect & Energy Engn DIAEE I-00197 Rome Italy Sapienza Univ Rome Dept Planning Design & Technol Architecture I-00197 Rome Italy

Ocean renewable wave power is one of the more encouraging inexhaustible energy sources, with the potential to be exploited for nearly 337 GW worldwide. However, compared with other sources of renewables, wave energy technologies have not been fully developed, and the produced energy price is not as competitive as that of wind or solar renewable technologies. In order to commercialise ocean wave technologies, a wide range of optimisation methodologies have been proposed in the last decade. However, evaluations and comparisons of the performance of state-of-the-art bio-inspired optimisation algorithms have not been contemplated for wave energy converters' optimisation. In this work, we conduct a comprehensive investigation, evaluation and comparison of the optimisation of the geometry, tether angles and power take-off (PTO) settings of a wave energy converter (WEC) using bio-inspired swarm-evolutionary optimisation algorithms based on a sample wave regime at a site in the Mediterranean Sea, in the west of Sicily, Italy. An improved version of a recent optimisation algorithm, called the Moth-Flame Optimiser (MFO), is also proposed for this application area. The results demonstrated that the proposed MFO can outperform other optimisation methods in maximising the total power harnessed from a WEC.

关键词： renewable energy systems wave energy converters power take-off bio-inspired meta-heuristics optimisation algorithms Moth Flame optimisation evolutionary algorithms swarm intelligence

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Mitigating Metaphors: A Comprehensible Guide to Recent Nature-Inspired algorithms

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SN Computer Science 2020年第1期1卷 49页

作者： Lones, Michael A. School of Mathematical and Computer Sciences Heriot-Watt University Edinburgh United Kingdom

In recent years, a plethora of new metaheuristic algorithms have explored different sources of inspiration within the biological and natural worlds. This nature-inspired approach to algorithm design has been widely criticised. A notable issue is the tendency for authors to use terminology that is derived from the domain of inspiration, rather than the broader domains of metaheuristics and optimisation. This makes it difficult to both comprehend how these algorithms work and understand their relationships to other metaheuristics. This paper attempts to address this issue, at least to some extent, by providing accessible descriptions of the most cited nature-inspired algorithms published in the last 20 years. It also discusses commonalities between these algorithms and more classical nature-inspired metaheuristics such as evolutionary algorithms and particle swarm optimisation, and finishes with a discussion of future directions for the field. © 2019, The Author(s).

关键词： Metaheuristics Nature-inspired algorithms optimisation algorithms Swarm computing

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A structured review of large language models in metaheuristic optimisation

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Decision Analytics Journal 2025年 15卷

作者： Reza Ghanbarzadeh Seyedali Mirjalili Faculty of Science and Engineering Southern Cross University Gold Coast Australia Centre for Artificial Intelligence Research and Optimisation Torrens University Australia Melbourne 3000 Australia Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava Czech Republic University Research and Innovation Center Obuda University Budapest 1034 Hungary

Metaheuristics are widely used to address complex optimisation problems where traditional exact methods are computationally infeasible or insufficiently flexible. With the rapid advancement of artificial intelligence, large language models, such as ChatGPT, Claude, Gemini, and LLaMA, have emerged as powerful tools capable of enhancing, automating, and adapting various stages of the optimisation process. This systematic literature review investigates the evolving role of large language models in metaheuristic optimisation, with a focus on algorithm generation, parameter tuning, hybridisation, constraint handling, and multi-objective optimisation. Following PRISMA guidelines, 25 studies from nine major scientific databases were selected and analysed. Through thematic analysis, a novel role-based taxonomy was developed that categorises large language model contributions into four functional roles: Advisor, Refiner, Enhancer, and Innovator. The findings demonstrate that large language models support the automation of metaheuristic workflows, enable dynamic adaptation, and contribute to the creation of novel heuristic strategies. Despite these advantages, the review also identifies persistent limitations, including prompt sensitivity, computational overhead, and scalability challenges. These issues highlight the need for more robust evaluation frameworks and benchmarking practices. This review offers a comprehensive synthesis of the current landscape, highlights research gaps, and provides actionable insights for researchers and practitioners aiming to integrate large language models into advanced optimisation systems across domains such as engineering, logistics, and computational design.

关键词： Systematic literature review optimisation algorithms Large language models Swarm intelligence Metaheuristic Generative AI ChatGPT LLM

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Implementation of a combinatorial-optimisation-based threat evaluation and jamming allocation system

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IET RADAR SONAR AND NAVIGATION 2019年第10期13卷 1636-1645页

作者： You, Shixun Diao, Ming Gao, Lipeng Harbin Engn Univ Dept Informat & Commun Engn Harbin 150001 Heilongjiang Peoples R China

Electromagnetic warfare is the most extensive and most hidden theatre of battle in modern warfare. To enhance the jamming effectiveness of a cooperative jammer platform against the threat of a radar net, a combinatorial-optimisation-based threat evaluation and jamming allocation (COTEJA) system is proposed. This COTEJA system fully considers the confrontation analysis in the jammer-radar process, including the interactions between radars, jammers, and jammer-radar pairs, and emphasises the realisation of cooperative jamming strategies. The cooperative jamming strategies include the combination of jamming techniques and optimisation algorithms for the objective function. The performance of the COTEJA system is evaluated through a combat mission that considers a platform with four jammers attacking five threats. In addition, the extended permutation-based differential evolution algorithm is used for the first time to optimise the jamming coding matrix, which effectively reduces the danger value of netted radar under multiple constraints. The numerical results reveal that the COTEJA system can make the optimal jamming decision within 1 s, which improves the survival ability of the platform in a complicated electromagnetic environment.

关键词： jamming optimisation evolutionary computation COTEJA system jammers extended permutation-based differential evolution algorithm jamming coding matrix netted radar optimal jamming decision combinatorial-optimisation-based threat evaluation jamming allocation system electromagnetic warfare modern warfare jamming effectiveness jammer platform radar net jammer-radar process radars jammer-radar pairs jamming strategies optimisation algorithms time 1 0 s

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Robust lane-detection algorithm based on improved symmetrical local threshold for feature extraction and inverse perspective mapping

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IET IMAGE PROCESSING 2019年第6期13卷 975-982页

作者： Ozgunalp, Umar Near East Univ Elect & Elect Engn Near East Blvd Nicosia Cyprus

Here, an extended version of the symmetrical local threshold (SLT) algorithm is introduced for lane feature extraction and used in a novel lane-detection system. The introduced feature map extractor utilises parallel lane border features as well as the dark-light-dark (DLD) pattern of the lane marking used in SLT. Hence, compared to the SLT, the true positive to positive rate of the calculated feature maps is increased from 69% to 86% on the ROMA dataset. In addition, the proposed algorithm supplies orientation information for the estimated feature points, which can be useful for many optimisation algorithms. Consequently, based on the estimated lane feature orientations, a global lane orientation is calculated and used for both enhancing the feature map and estimating a one-dimensional (1D) lateral offset likelihood function. Then, the estimated 1D functions are filtered temporally and up to two linear lane candidates are detected. For increased flexibility, robust fitting is applied to the feature points in the region of interest (ROI). Finally, based on the detection of the previous frame, a mask is created and applied to the next frame. When tested on 2301 road images, mean error in lateral offset is calculated as 4.1 pixel on the IPM images.

关键词： feature extraction driver information systems traffic engineering computing road vehicles IPM images road images ROI region of interest lane feature orientations 1D function estimation feature point estimation parallel lane border features feature map extractor orientation information linear lane candidates global lane orientation optimisation algorithms dark-light-dark pattern lane feature extraction SLT symmetrical local threshold algorithm inverse perspective mapping improved symmetrical local threshold robust lane-detection algorithm

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Design methodologies for the output power maximisation of synchronous reluctance machines

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IET ELECTRIC POWER APPLICATIONS 2019年第8期13卷 1131-1140页

作者： Palmieri, Marco Cascella, Giuseppe Leonardo Cupertino, Francesco Politecn Bari Dept Elect Engn & Informat Technol Via E Orabona 4 Bari Italy

Synchronous reluctance (SyR) machines can constitute a promising alternative to permanent magnet machines for low-cost applications. The recent literature reports some guidelines for choosing the proper number and position of the rotor flux barriers capable of enhancing the electromagnetic performance in low-speed applications. However, as the rotational speed increases, the electromagnetic and structural mutual interactions become relevant;therefore, an optimal design requires a proper trade-off between torque production and stress reduction, which can be difficultly predicted analytically. This work proposes an approach based on optimisation algorithms in order to find 'non-conventional' geometries able to improve the power density: genetic algorithms coupled to magneto-static finite elements analysis and structural analytical models, are adopted to co-design SyR machines with different numbers of stator slots and rotor barriers subjected to the same thermal constraints. This study investigates two design procedures aimed at maximising the output power of SyR machines by increasing the rotational speed. Both procedures allow determining the power limits for a given volume of active parts and a fixed amount of admissible losses;moreover, the second procedure automatically finds also the rotational speed which maximises the output power.

关键词： permanent magnet machines finite element analysis rotors torque optimisation genetic algorithms stators reluctance machines design methodologies output power maximisation synchronous reluctance machines promising alternative permanent magnet machines low-cost applications proper number position rotor flux barriers electromagnetic performance low-speed applications rotational speed increases electromagnetic interactions structural mutual interactions optimal design proper trade-off between torque production stress reduction optimisation algorithms nonconventional geometries power density genetic algorithms magneto-static finite elements analysis structural analytical models co-design SyR machines different numbers rotor barriers design procedures power limits

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Scenario-based multi-objective optimisation with loadability in islanded microgrids considering load and renewable generation uncertainties

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IET RENEWABLE POWER GENERATION 2019年第5期13卷 785-800页

作者： Jithendranath, J. Das, Debapriya Indian Inst Technol Kharagpur Dept Elect Engn Kharagpur 721302 W Bengal India

Operation of microgrids in islanded mode either by intention or by involuntary action is of increasing concern nowadays. Optimal operation and control of such islanded microgrids considering various objectives are crucial for effective planning problem. This work proposes a new methodology for optimal operation of islanded microgrids considering economic and emission objectives together with loadability in droop-regulated islanded microgrid. Loadability being one of dominant aspects to be considered for effective microgrid planning and operation to ensure increased voltage-stability margin in the entire due course of operation. In conjunction with that islanded microgrid operational constraints and uncertainty in various system parameters need to be considered to interpret real-time operation of the microgrid. In the light of above, a multi-objective optimisation problem in droop-regulated islanded microgrid is formulated with economic-emission-loadability objectives by considering uncertainties in load demand and renewable generation along with system constraints. The formulated problem is solved using multi-objective antlion optimiser algorithm and validated on the test system. The performance of the proposed approach is compared with other optimisation algorithms to show its effectiveness. The importance of considering loadability along with economic-emission objectives to achieve compromised solution resulted in ensuring better operational planning of droop-regulated islanded microgrids.

关键词： optimisation distributed power generation evolutionary computation considering loadability economic-emission objectives operational planning droop-regulated islanded microgrid scenario-based multiobjective optimisation islanded microgrids renewable generation uncertainties islanded mode optimal operation effective planning problem economic emission objectives effective microgrid planning islanded microgrid operational constraints real-time operation multiobjective optimisation problem economic-emission-loadability objectives optimiser algorithm optimisation algorithms

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Experimental study of the temperature variations in a standing wave loudspeaker driven thermoacoustic refrigerator

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2020年 17卷

作者： Alamir, Mahmoud A. Flinders Univ S Australia Coll Sci & Engn Clovelly Pk Adelaide SA 5042 Australia

The temperature difference across the stack is essential to the performance of thermoacoustic refrigerators. This paper experimentally investigates the effect of the stack geometric parameters on the temperature difference across the stack in a standing wave loudspeaker driven thermoacoustic refrigerator. In addition, it investigates the temperature variations through the resonator and its cross-sections. The effect of this variability on the performance of the refrigerator is also presented. Celcor Ceramic stacks are used at five normalised stack positions of 0.286, 0.764, 1.05, 1.43 and 1.72, four normalised stack lengths of 0.076, 0.114, 0.153 and 0.191, and two stack porosities of 0.8 and 0.85. Results show that the maximum and minimum temperatures through the resonator are across the stack, particularly at the centre point of each side of the stack. Moreover, at certain stack positions, hot and cold sides across the stack are altered. The coefficient of performance also increases at high-temperature difference positions. As a result, this study provides guidelines for increasing the performance of thermoacoustic refrigerators, which still lack competitiveness because of their relatively low performance. It also helps design some parts such as heat exchangers to consider the maximum and minimum temperature positions of thermoacoustic refrigerators.

关键词： Thermoacoustic refrigeration Temperature difference optimisation algorithms Oscillatory heat transfer Heat exchangers

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