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Solving unit commitment problem using a novel version of harmony search algorithm

Roozbeh MORSALI,Tohid JAFARI,Amirhossein GHODS,Mohammad KARIMI

《能源前沿（英文）》 2014年第8卷第3期页码 297-304 doi: 10.1007/s11708-014-0309-7

摘要： In this context, a novel structure was proposed for improving harmony search (HS) algorithm to solve the unit comment (UC) problem. The HS algorithm obtained optimal solution for defined objective function by improvising, updating and checking operators. In the proposed improved self-adaptive HS (SGHS) algorithm, two important control parameters were adjusted to reach better solution from the simple HS algorithm. The objective function of this study consisted of operation, start-up and shut-down costs. To confirm the effectiveness, the SGHS algorithm was tested on systems with 10, 20, 40 and 60 generating units, and the obtained results were compared with those of the simple HS algorithm and other related works.

关键词： generation scheduling harmony search (HS) algorithm intelligent technique unit commitment

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一种改进的和声搜索算法及其在权重模糊产生式规则获取中的应用 Research Article

叶绍强1,周恺卿1,Azlan Mohd ZAIN2,王方岭1,Yusliza YUSOFF2

《信息与电子工程前沿（英文）》 2023年第24卷第11期页码 1574-1590 doi: 10.1631/FITEE.2200334

摘要：和声搜索算法(harmony search, HS)是一种随机元启发式算法，其灵感来自于音乐家的即兴创作过程。针对HS在求解中易陷入局部极值等不足，本文提出一种混合布谷鸟算子的改进的和声布谷鸟搜索算法(modified HS with a hybrid cuckoo search (CS) operator,HS-CS)增强全局搜索能力。该算法首先对HS音高扰动调整方法的随机性进行分析，根据和声库中解的质量生成自适应惯性权重，并重构微调带宽寻优，提升HS的寻优效率及精度。通过证明3个定理揭示HS-CS是一种全局收敛的元启发式算法。在实验部分，选取12种经典的测试函数优化求解以验证HS-CS算法的性能。

关键词：和声搜索算法；布谷鸟搜索算法；全局收敛；函数优化；权重模糊产生式规则抽取

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Optimal operation of microgrid using hybrid differential evolution and harmony search algorithm

S. SURENDER REDDY,Jae Young PARK,Chan Mook JUNG

《能源前沿（英文）》 2016年第10卷第3期页码 355-362 doi: 10.1007/s11708-016-0414-x

摘要： This paper proposes the generation scheduling approach for a microgrid comprised of conventional generators, wind energy generators, solar photovoltaic (PV) systems, battery storage, and electric vehicles. The electrical vehicles (EVs) play two different roles: as load demands during charging, and as storage units to supply energy to remaining load demands in the MG when they are plugged into the microgrid (MG). Wind and solar PV powers are intermittent in nature; hence by including the battery storage and EVs, the MG becomes more stable. Here, the total cost objective is minimized considering the cost of conventional generators, wind generators, solar PV systems and EVs. The proposed optimal scheduling problem is solved using the hybrid differential evolution and harmony search (hybrid DE-HS) algorithm including the wind energy generators and solar PV system along with the battery storage and EVs. Moreover, it requires the least investment.

关键词： battery storage electric vehicles (EVs) microgrid (MG) optimal scheduling solar photovoltaic (PV) system wind energy conversion system

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Compressive strength prediction and optimization design of sustainable concrete based on squirrel searchalgorithm-extreme gradient boosting technique

《结构与土木工程前沿（英文）》页码 1310-1325 doi: 10.1007/s11709-023-0997-3

摘要： Concrete is the most commonly used construction material. However, its production leads to high carbon dioxide (CO₂) emissions and energy consumption. Therefore, developing waste-substitutable concrete components is necessary. Improving the sustainability and greenness of concrete is the focus of this research. In this regard, 899 data points were collected from existing studies where cement, slag, fly ash, superplasticizer, coarse aggregate, and fine aggregate were considered potential influential factors. The complex relationship between influential factors and concrete compressive strength makes the prediction and estimation of compressive strength difficult. Instead of the traditional compressive strength test, this study combines five novel metaheuristic algorithms with extreme gradient boosting (XGB) to predict the compressive strength of green concrete based on fly ash and blast furnace slag. The intelligent prediction models were assessed using the root mean square error (RMSE), coefficient of determination (R²), mean absolute error (MAE), and variance accounted for (VAF). The results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yielded the best overall prediction performance with R² values of 0.9930 and 0.9576, VAF values of 99.30 and 95.79, MAE values of 0.52 and 2.50, RMSE of 1.34 and 3.31 for the training and testing sets, respectively. The remaining five prediction methods yield promising results. Therefore, the developed hybrid XGB model can be introduced as an accurate and fast technique for the performance prediction of green concrete. Finally, the developed SSA-XGB considered the effects of all the input factors on the compressive strength. The ability of the model to predict the performance of concrete with unknown proportions can play a significant role in accelerating the development and application of sustainable concrete and furthering a sustainable economy.

关键词： sustainable concrete fly ash slay extreme gradient boosting technique squirrel search algorithm parametric analysis

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Estimation of optimum design of structural systems via machine learning

《结构与土木工程前沿（英文）》 2021年第15卷第6期页码 1441-1452 doi: 10.1007/s11709-021-0774-0

摘要： Three different structural engineering designs were investigated to determine optimum design variables, and then to estimate design parameters and the main objective function of designs directly, speedily, and effectively. Two different optimization operations were carried out: One used the harmony search (HS) algorithm, combining different ranges of both HS parameters and iteration with population numbers. The other used an estimation application that was done via artificial neural networks (ANN) to find out the estimated values of parameters. To explore the estimation success of ANN models, different test cases were proposed for the three structural designs. Outcomes of the study suggest that ANN estimation for structures is an effective, successful, and speedy tool to forecast and determine the real optimum results for any design model.

关键词： optimization metaheuristic algorithms harmony search structural designs machine learning artificial neural networks

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Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

《结构与土木工程前沿（英文）》 2023年第17卷第3期页码 378-395 doi: 10.1007/s11709-022-0899-9

摘要： This paper presents a combined method based on optimized neural networks and optimization algorithms to solve structural optimization problems. The main idea is to utilize an optimized artificial neural network (OANN) as a surrogate model to reduce the number of computations for structural analysis. First, the OANN is trained appropriately. Subsequently, the main optimization problem is solved using the OANN and a population-based algorithm. The algorithms considered in this step are the arithmetic optimization algorithm (AOA) and genetic algorithm (GA). Finally, the abovementioned problem is solved using the optimal point obtained from the previous step and the pattern search (PS) algorithm. To evaluate the performance of the proposed method, two numerical examples are considered. In the first example, the performance of two algorithms, OANN + AOA + PS and OANN + GA + PS, is investigated. Using the GA reduces the elapsed time by approximately 50% compared with using the AOA. Results show that both the OANN + GA + PS and OANN + AOA + PS algorithms perform well in solving structural optimization problems and achieve the same optimal design. However, the OANN + GA + PS algorithm requires significantly fewer function evaluations to achieve the same accuracy as the OANN + AOA + PS algorithm.

关键词： optimization surrogate models artificial neural network SAP2000 genetic algorithm

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一种新的融合本体和主机信息的改进禁忌搜索算法的主题爬虫方法 Research Article

刘景发1,王震1,2,钟国1,杨志和1

《信息与电子工程前沿（英文）》 2023年第24卷第6期页码 859-875 doi: 10.1631/FITEE.2200315

摘要：为解决传统主题爬虫方法存在的主题描述不完整和重复爬取已访问链接的问题，本文提出一种新的融合本体和主机信息的改进禁忌搜索算法的主题爬虫方法（FCITS_OH）。该方法基于形式概念分析（FCA）构建领域本体，在语义和知识层面描述主题。为避免重复爬取已访问的链接和扩大搜索范围，提出一种改进的禁忌搜索（ITS）算法和记忆主机信息的策略。此外，为改进未访问链接的主题相关性的评估方法，提出一种基于Web文本和链接结构的综合优先度评估方法。以旅游和暴雨灾害为主题的实验结果表明，对于不同的性能指标，所提出的爬虫方法优于文献中其它主题爬虫策略。

关键词：主题爬虫；禁忌搜索算法；本体；主机信息；优先度评估

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Influence of HS and NH on biogas dry reforming using Ni catalyst: a study on single and synergetic effect

《环境科学与工程前沿（英文）》 2023年第17卷第3期 doi: 10.1007/s11783-023-1632-1

摘要：

● NH₃ in biogas had a slight inhibitory effect on dry reforming.

关键词： Biogas Dry reforming Sulfur poisoning Ammonia Synergetic effect Hydrogen

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A simple multi-wave algorithm for the uncapacitated facility location problem

Fred GLOVER, Saïd HANAFI, Oualid GUEMRI, Igor CREVITS

《工程管理前沿（英文）》 2018年第5卷第4期页码 451-465 doi: 10.15302/J-FEM-2018038

摘要：

The multi-wave algorithm (Glover, 2016) integrates tabu search and strategic oscillation utilizing repeated waves (nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem (UFLP) to minimize the combined costs of selecting facilities to be opened and of assigning each customer to an opened facility in order to meet the customers’ demands. The objective is to minimize the overall cost including the costs of opening facilities and the costs of allocations. Our experimental tests on a standard set of benchmarks for this widely-studied class of problems show that our algorithm outperforms all previous methods.

关键词： discrete optimization UFLP multi-wave optimization strategic oscillation tabu search

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MSSSA：一种针对全局优化问题的多策略增强型麻雀搜索算法 Research Article

孟凯1,2,陈晨1,2,辛斌1,2

《信息与电子工程前沿（英文）》 2022年第23卷第12期页码 1828-1847 doi: 10.1631/FITEE.2200237

摘要：麻雀搜索算法(SSA)是一种新的元启发式优化方法，具有简单和灵活的优点。然而，在处理多模态优化问题时，该算法仍存在早熟收敛、探索与开发不平衡等缺陷。针对上述问题，本文提出一种多策略增强的麻雀搜索算法(MSSSA)。首先，引入混沌映射以获取高质量的初始种群，并采用对立学习策略增加种群的多样性。其次，设计了一种自适应参数控制策略，以在全局探索与局部开发之间保持适当的平衡。最后，在个体更新阶段嵌入混合扰动机制，以避免算法陷入局部最优。为了验证所提方法的有效性，在IEEE CEC2014和IEEE CEC2019测试集的40个函数，以及10个不同维度的经典函数上进行了大量的实验。实验结果表明，与一些先进的算法相比，所提出的MSSSA表现出突出的优化性能。该算法还成功地应用于两个工程优化问题，证明了MSSSA在解决实际问题方面的优越性。

关键词：群智能；麻雀搜索算法；自适应参数控制策略；混合扰动机制；优化问题

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基于嵌入协作的多方法协作优化方法

罗文彩,罗世彬,王振国

《中国工程科学》 2004年第6卷第4期页码 51-55

摘要：

提出一种基于嵌入协作的多方法协作优化方法。算法采用嵌入方式组织各个优化方法之间的协作，利用优化方法之间的协作效应提高优化性能。进行遗传算法、模式搜索法和Powell法嵌入协作组成的多方法协作优化方法设计。计算实例表明，基于嵌入协作的多方法协作优化方法取得了优于单个优化方法的全局最优特性。

关键词：多方法协作优化方法嵌入协作遗传算法模式搜索法 Powell法

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Mechanism insight into the formation of HS from thiophene pyrolysis: A theoretical study

《环境科学与工程前沿（英文）》 2021年第15卷第6期 doi: 10.1007/s11783-021-1404-8

摘要：

• Possible formation pathways of H₂S were revealed in thiophene pyrolysis.

关键词： Density functional theory Waste rubber Thiophene H₂S Pyrolysis

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VALORIZATION OF BIOGAS THROUGH SIMULTANEOUS CO AND HS REMOVAL BY RENEWABLE AQUEOUS AMMONIA SOLUTION IN

《农业科学与工程前沿（英文）》 2023年第10卷第3期页码 468-478 doi: 10.15302/J-FASE-2022473

摘要：

● Simultaneous H₂S and CO₂ removal from biogas is studied.

关键词： biomethane biogas purification CO₂ removal H₂S removal membrane absorption

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一种改进的果蝇优化算法及其在旅行商问题求解中的应用 Article

Lan HUANG, Gui-chao WANG, Tian BAI, Zhe WANG

《信息与电子工程前沿（英文）》 2017年第18卷第10期页码 1525-1533 doi: 10.1631/FITEE.1601364

摘要：旅行商问题（traveling salesman problem, TSP）是经典的NP（non-deterministic polynomial）难问题，在实际工程中有许多应用。而果蝇优化算法作为一种用于求解TSP问题的新群智能算法，具有易于理解、实现简单等优点。然而，该算法收敛速度慢、易陷入局部最优，从而导致寻优精度不高。为了有效求解TSP问题，本文提出了三种改进方法，以优化果蝇算法在TSP求解中的应用。一是，更加注重果蝇觅食行为中的视觉搜索能力，从而增强果蝇算法的收敛能力；二是，在果蝇优化算法中融入了淘汰机制以增加种群多样性；三是，提出了逆序操作算子和乘法操作算子，并将这两种基本操作算子运用到果蝇算法求解TSP问题上。本文对TSPLIB中的10个算例进行仿真实验，并与其它算法的实验结果进行对比，结果证明该算法不仅收敛速度快，而且寻优精度高。

关键词：旅行商问题；果蝇优化算法；淘汰机制；视觉搜索；操作算子

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A Cu-modified active carbon fiber significantly promoted HS and PH simultaneous removal at a low reaction

《环境科学与工程前沿（英文）》 2021年第15卷第6期 doi: 10.1007/s11783-021-1425-3

摘要：

• Cu_0.15-ACF performs the best for H₂S and PH₃ simultaneous removal.

关键词： ACF H₂S PH₃ Cu Low temperature Simultaneous removal