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Enhanced harmony search algorithm with non-linear control parameters for global optimization and engineering design problems

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ENGINEERING WITH COMPUTERS 2022年第SUPPL 4期38卷 3539-3562页

作者： Gupta, Shubham Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

harmony search algorithm (HSA), inspired by the behaviors of music improvisation process, is a widely used metaheuristic to solve global optimization problems arises in various fields. The reason of its popularity is its simplicity of algorithm structure and good performance. However, the conventional harmony search algorithm (HSA) experiences prone towards the local optima, tedious task of tuning parameters, and premature convergence. To overcome all these drawbacks of conventional HSA and further improve the precision of numerical results, a new variant of the HSA called modified harmony search algorithm (MHSA) is proposed in the present study. This MHSA utilizes the valuable information stored in the harmony memory and modifies the search strategy to make an efficient search procedure by adopting a new formulation to the pitch adjustment process, randomization process, harmony memory considering rate (HMCR), and pitch adjustment rate (PAR). The experimental validation and comparative performance study with conventional HSA, variants of HSA such as adaptive harmony search with best based search strategy (ABHS), enhanced self-adaptive global-best harmony search (ESGHS), novel self-adaptive harmony search (NSHS), parameter adaptive harmony search (PAHS), Gaussian global-best harmony search algorithm (GGHS) and other metaheuristics such as sine cosine algorithm (SCA), grey wolf optimizer (GWO), comprehensive learning particle swarm optimization (CLPSO), gbest-guided artificial bee colony (GABC), and covariance matrix adaptation evolution strategy (CMA-ES) is conducted on a set of 23 well-known benchmark problems. In addition to this benchmarking, the proposed MHSA is also used to solve three structural engineering design problem. The statistical test and convergence behaviour analysis are used to analyze the quality of search and significance of improved accuracy. The comparison illustrates the superior search efficiency of the proposed MHSA than other algorithms as

关键词： Optimization harmony search algorithm Exploration and exploitation

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Multi-objective stock market portfolio selection using multi-stage stochastic programming with a harmony search algorithm

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NEURAL COMPUTING & APPLICATIONS 2022年第24期34卷 22257-22274页

作者： Asgari, H. Behnamian, J. Bu Ali Sina Univ Fac Engn Dept Ind Engn Hamadan Hamadan Iran

The problem of stock portfolio selection is one of the most critical problems in financial markets. The portfolio selection problem is to find an optimal solution to allocate a fixed amount of capital to a set of available stocks with the objective function of having the maximum expected rate of return and, at the same time, the least possible risk. Among the shortcomings that most stock portfolio models have is not paying attention to future changes and focusing too much on past information. This study aims to provide a framework that addresses some shortcomings and provides a practical tool. In this regard, this study suggests a multi-objective and multi-stage stochastic model for portfolio selection in the financial market. The stage refers to the periods in which the stock portfolio will be reviewed. By combining the scenario generation model with multi-stage stochastic programming, the investor is expected to achieve a suitable solution based on past information and various future scenarios. To solve the proposed model, a meta-heuristic algorithm whose main idea is derived from the harmony search algorithm is proposed. Finally, numerical instances were utilized by the use of real stock information from the Iranian stocks market. The algorithm proposed in this research was compared with a genetic algorithm in terms of the quality of the generated solutions and the runtime of the algorithms, and the superiority of the proposed algorithm has been proven.

关键词： Portfolio selection Multi-stage stochastic programming Multi-objective optimization harmony search algorithm

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A Dual-Strategy Contest harmony search algorithm Based on Population State for the System Reliability-Redundancy Allocation Problems 14th

A Dual-Strategy Contest Harmony Search Algorithm Based on Po...

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14th International Conference on Swarm Intelligence (ICSI)

作者： Liang, Siqi He, Chang Ouyang, Haibin Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou Peoples R China

ISBN: (纸本)9783031366215;9783031366222

At present, many improved algorithms have effectively improved the ability to converge to the optimal value. However, there are still difficulties: how to effectively balance the deep development ability of the algorithm in a small range and the extensive exploration ability in the global search field in the iterative process. For this reason, this topic first proposes a population state evaluation indicator, which continuously detects the state and diversity of the population with iteration. On this basis, the dual-strategy competition mechanism is adopted. Through the population state evaluation index, the strategy can select a strategy that is more conducive to rapid convergence according to the changes of the population during the iteration process. Through the advantage competition of the two strategies, the development ability of the algorithm has been steadily and persistently improved. However, there is still the risk of falling into the local optimal dilemma. Therefore, the change of population diversity is considered in the evaluation index of population status in this study. In order to further increase the activity of the global search range, the computational individuals used in the proposed environmental assessment index of population diversity are randomly selected. In general, in the greedy comparison of the two strategies, this study still ensures the consideration and influence of diversity, and effectively balances the ability of algorithm exploration and development.

关键词： harmony search algorithm Dual-strategy contest mechanism Population state evaluation Diversity evaluation System reliability

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Power Grid Project Portfolio Decision-Making Based on harmony search algorithm 8

Power Grid Project Portfolio Decision-Making Based on Harmon...

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8th International Conference on Power Energy Systems and Applications, ICoPESA 2024

作者： Qin, Huaqin Jia, Jinwei Han, Yu Wang, Hongyue Liu, Hui Beijing Kedong Electric Power Control System Co. LTD. Beijing China North China Electric Power University Beijing China

ISBN: (纸本)9798350351668

With the power grid enterprises will pay more attention to the return on investment and the benefits of investment. Investing from the perspective of efficiency, giving full play to the advantages of various resources, and maximizing the balance of multiple demands within a reasonable range to obtain the maximum return on investment are the goals pursued by enterprises. This paper establishes a model for measuring the investment benefits of power grid projects, evaluates the benefits of power grid projects from three dimensions, and supports the investment decision of power grid projects. According to the evaluation results, the projects with better benefits are screened out as alternative projects, and the investment portfolios of multiple alternative projects are optimized, with the goal of achieving the maximum comprehensive benefits, integrating the investment demand, investment capacity, project constraints and resource constraints, and constructing the optimization model of grid investment, and finally determining the investment portfolio scheme with the maximum comprehensive benefits. © 2024 IEEE.

关键词： evaluation system harmony search algorithm investment decisions power grid projects project benefits

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Implementing an Optimal Energy Management System for a Set of Microgrids Using the harmony search algorithm

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Energy Engineering 2022年第5期119卷 1843-1860页

作者： Xiangjian Shi Teng Liu WeiMu Jianfeng Zhao School of Electrical Engineering Southeast UniversityNanjing210096China NR Electric Co. Ltd.Nanjing211106China

A microgrid(MG)refers to a set of loads,generation resources and energy storage systems acting as a controllable load or a generator to supply power and heating to a local *** MG-generated power management is a central topic for MG design and *** existence of dispersed generation(DG)resources has faced MG management with new *** on the level of exchanges between an MG and the main grid,the MG operation states can be divided into independent or grid-connected *** management in MGs aims to supply power at the lowest cost for optimal load *** study examines MG energy management in two operational modes of islanded and grid-connected,and proposes a structure with two control layers(primary and secondary)for energy *** the principal level of control,the energy management system is determined individually for all MG by taking into consideration the probability constraints and RES uncertainty by the Weibull the probability density function(PDF),generation resources’power as well as the generation surplus and deficit of each ***,the information of the power surplus and deficit of each MG must be sent to the central energy management *** confirm the proposed structure,a case system with two MGs and a condensive load is simulated by using a multi-time harmony search *** scenarios are applied to evaluate the performance of this *** findings clearly show the effectiveness of the proposed system in the energy management of several MGs,leading to the optimal performance of the resources per ***,the proposed control scheme properly controls the MG and grid’s performance in their interactions and offers a high level of robustness,stable behavior under different conditions and high quality of power supply.

关键词： harmony search algorithm multi-MG system multi-owner systems central and non-central control optimal energy management uncertainty

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Probabilistic harmony search algorithm: Fitness Proportionate Selection Variants 1st

Probabilistic Harmony Search Algorithm: Fitness Proportionat...

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1st International Conference on Intelligent Systems and Applications

作者： Yadav, Ravi Vullamparthi, Sumanth Tapadia, Aashi Kulkarni, Anand J. Kale, Preeti Dr Vishwanath Karad MIT World Peace Univ Sch CET Pune Maharashtra India Dr Vishwanath Karad MIT World Peace Univ Inst Artificial Intelligence Pune Maharashtra India

ISBN: (纸本)9789811965814;9789811965807

harmony search algorithm is a meta-heuristic, nature-inspired optimization algorithm that tries to mimic real-life improvisations that musicians use to generate a harmony that is more pleasing to hear. This paper presents and compares three different types of harmony search algorithms. We start with the implementation of the original HSA. Further, two different modifications were made to the original HSA, the first one uses fitness proportionate selection of harmonies from the HM and is known as biased Roulette harmony search algorithm (BRHSA) and the second one builds on BRHSA by adding simple mathematics to further guide the algorithm toward the desired solution and is called guided biased Roulette harmony search algorithm (GBRHSA). These three variants of HSA were applied on four benchmark test functions on the same machine, and the results obtained after 30 runs were noted down for comparison. It was observed that the results given by the three variants had no specific trend in terms of best result or computational time and the performance of a particular variant was subject to parameters like the kind of function and its search domain. The results presented in this paper can be used as a foundation for the future works that will be done on this algorithm and can help derive an apt variant of HSA for solving a particular problem.

关键词： harmony search algorithm Fitness proportionate selection Biased Roulette wheel Guided biased Roulette wheel Benchmark test functions Comparison

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Intrusion Detection System using Long Short Term Memory Classification, Artificial Raindrop algorithm and harmony search algorithm

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2022年第12期13卷 95-103页

作者： Raj, Meghana G. Pani, Santosh Kumar Kalinga Inst Ind Technol Deemed Univ Dept Sch Comp Engn Bhubaneswar India

Nowadays, various technological advancements in Intrusion Detection Systems (IDS) detects the malicious attacks and reinstate network security in the cloud platform. Cloud based IDS designed with hybrid elements combining Machine Learning and Computational Intelligence algorithms have been shown to perform better on parameters, such as Detection Rate, Accuracy, and the False Positive Rate. Machine Learning algorithms provide effective techniques for classification and prediction of network attacks, by analyzing existing IDS datasets. The main challenge is selection of appropriate data dimensions to be used for detection of attacks, out of the high number of data dimensions available. For the selected data dimensions, Computational Intelligence algorithms provide effective techniques for hyper-parameter tuning, by optimizing on reiterative basis. The main challenge is selection of appropriate algorithm which offers optimal performance results. In this research, Hybrid Meta-heuristic approach, which combines a Long Short Term Memory (LSTM) classification model in dimension selection, with the application of Artificial Raindrop algorithm-harmony search algorithm (ARA-HSA) for hyper -parameter tuning, in order to achieve a high performance IDS in cloud environment. The performance validation of the hybrid LSTM-ARA-HSA algorithm has been carried out using a benchmark IDS data set and the comparative results for this algorithm along with other recent hybrid approaches has been presented.

关键词： Artificial raindrop algorithm cloud computing harmony search algorithm hybrid meta-heuristic algorithms hyper-parameter tuning intrusion detection system long short term memory classification model

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Annealing harmony search algorithm to Solve the Nurse Rostering Problem

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Computers, Materials & Continua 2022年第6期71卷 5545-5559页

作者： Mohammed Hadwan Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Intelligent Analytics Group(IAG) College of ComputerQassim UniversityBuraydahSaudi Arabia

A real-life problem is the rostering of nurses at *** is a famous nondeterministic,polynomial time(NP)-hard combinatorial optimization *** the real-world nurse rostering problem(NRP)constraints in distributing workload equally between available nurses is still a difficult task to *** international shortage of nurses,in addition to the spread of COVID-19,has made it more difficult to provide convenient rosters for *** on the literature,heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity,especially for large ***-based algorithms in general have problems striking the balance between diversification and ***,this paper aims to introduce a novel metaheuristic hybridization that combines the enhanced harmony search algorithm(EHSA)with the simulated annealing(SA)algorithm called the annealing harmony search algorithm(AHSA).The AHSA is used to solve NRP from a Malaysian *** AHSA performance is compared to the EHSA,climbing harmony search algorithm(CHSA),deluge harmony search algorithm(DHSA),and harmony annealing search algorithm(HAS).The results show that the AHSA performs better than the other compared algorithms for all the tested instances where the best ever results reported for the UKMMC dataset.

关键词： harmony search algorithm simulated annealing combinatorial optimization problems timetabling metaheuristic algorithms nurse rostering problems

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Prediction of TBM Penetration Rate Using Fuzzy Logic, Particle Swarm Optimization and harmony search algorithm

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GEOTECHNICAL AND GEOLOGICAL ENGINEERING 2022年第3期40卷 1513-1536页

作者： Afradi, Alireza Ebrahimabadi, Arash Hallajian, Tahereh Islamic Azad Univ Dept Min & Geol Qaemshahr Branch Qaemshahr Iran

Tunnel Boring Machine (TBM) penetration rate prediction is one of the most important problem in tunneling projects. Estimating of Tunnel Boring Machine (TBM) penetration rate can considerably reduce the costs of tunneling projects. In this study, Datasets including Uniaxial Compressive Strength, Brazilian Tensile Strength, Density and Joint Angle as input parameters and Rate of Penetration as an output parameter. The aim of this study is estimating the penetration rate of tunnel boring machines using fuzzy logic method, harmony search algorithm (HSA) and Particle Swarm Optimization (PSO) in the Nosoud water conveyance Tunnel. The modeling results showed that the fuzzy model has a significant advantage over the PSO and HSA.

关键词： Tunnel boring machine Penetration rate Fuzzy logic Particle swarm optimization harmony search algorithm Nosoud water conveyance tunnel

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Modeling the Proposal of the Simultaneous Purchases and Sales of Electricity and Gas for the Energy Market in a Microgrid Using the harmony search algorithm

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Energy Engineering 2022年第6期119卷 2681-2709页

作者： Zinan Zhou Yirun Chen Wensheng Dai Financial School China Financial Policy Research CenterInternational Money InstituteRenmin University of ChinaBeijing100872China

The use of different energy carriers together,known as an energy hub,has been a hot topic of research in recent years amongst scientists and *** term energy hub refers to the simultaneous operation of various infrastructures for energy generation and transfer,which has gained momentum in the form of microgrids(MGs).This paper introduces a new strategy for the optimal performance of an MG consisting of different energy carriers for each *** a smart distribution network(DN),MGs can reduce their own costs in the previous-day market by bidding on sales and *** sales and purchases bidding problem is challenging due to different uncertainties,*** paper proposes a two-stage strategy for making an optimal bid on electricity sales and purchases with electricity and gas price dependency in the previous-day and real-time markets for an energy *** this model,the MG behavior regarding the electricity and gas energy sales/purchase,the simultaneous effects of electricity and gas prices,as well as the energy carriers’dependence on one another are all *** to the inherent uncertainty in the sources of clean energy production,the probabilistic model and the production and reduction scenario have been used in the paper to cover this *** the proposed grid,energy sales/purchases are presented in a multi-carrier MG in a two-stage *** model is solved by using the harmony search algorithm in *** results demonstrate the benefits of this model in reducing energy hub costs of operation.

关键词： Energy management energy market operation multi-carrier microgrids uncertainty harmony search algorithm HSA microgrids MGs distribution network DN MATLAB

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