检索结果-内蒙古大学图书馆

An Enhanced harmony search algorithm for Cascade Reservoirs Planning 1

17th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP) / 14th International Conference on Frontiers of Information Technology, Applications and Tools (FITAT)

作者： Dao, Thi-Kien Nguyen, Thi-Xuan-Huong Vu, Ngoc-Thanh Nguyen, Trong-The Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fujian Peoples R China Univ Management & Technol Haiphong Haiphong Vietnam Haiphong Univ Med & Pharm Haiphong Vietnam VNUHCM Univ Informat Technol Multimedia Communicat Lab Ho Chi Minh City Vietnam

ISBN: (数字)9789811910531

ISBN: (纸本)9789811910531;9789811910524

A fair, efficient, and reasonable strategy for benefit transfer to multi-stakeholders is critical for preserving cooperation stability and development sustainability for cascade reservoirs under current comprehensive watershed development. This research proposes a novel approach to cascade reservoir planning that considers the need for multi-objective water resource development and benefit distribution to multiple stakeholders. The cascade reservoirs planning is modeled as the optimal dispatching model function and optimized by applying an enhanced harmony search algorithm (EHSA). Compared results with the previous methods show that the proposed method with EHSA produces total power generation higher and the calculation time faster convergence speed, respectively, than other competitive methods. The proposed method provides a feasible way to solve the optimal dispatching model of cascade reservoir planning in power generation.

关键词： Cascade reservoir Chaotic sequence harmony search algorithm Optimal operation planning Uniform design

来源：评论

学校读者我要写书评

暂无评论

An improved harmony search algorithm using opposition-based learning and local search for solving the maximal covering location problem

引用

ENGINEERING OPTIMIZATION 2024年第8期56卷 1298-1317页

作者： Atta, Soumen Univ Nova Gorica Ctr Informat Technol & Appl Math Nova Gorica Slovenia

In this article, an improved harmony search algorithm (IHSA) that utilizes opposition-based learning is presented for solving the maximal covering location problem (MCLP). The MCLP is a well-known facility location problem where a fixed number of facilities are opened at a given potential set of facility locations such that the sum of the demands of customers covered by the open facilities is maximized. Here, the performance of the harmony search algorithm (HSA) is improved by incorporating opposition-based learning that utilizes opposite, quasi-opposite and quasi-reflected numbers. Moreover, a local search heuristic is used to improve the performance of the HSA further. The proposed IHSA is employed to solve 83 real-world MCLP instances. The performance of the IHSA is compared with a Lagrangean/surrogate relaxation-based heuristic, a customized genetic algorithm with local refinement, and an improved chemical reaction optimization-based algorithm. The proposed IHSA is found to perform well in solving the MCLP instances.

关键词： Maximal covering location problem harmony search algorithm opposition-based learning facility location problem opposite number

来源：评论

学校读者我要写书评

暂无评论

A Global harmony search algorithm Based on Tent Chaos Map and Elite Reverse Learning 14

A Global Harmony Search Algorithm Based on Tent Chaos Map an...

引用

14th International Conference on Advanced Computational Intelligence

作者： Liu, Tianqi Yang, Hua Yu, Jing Zhou, Kang Jiang, Feng Wuhan Polytech Univ Sch Math & Comp Sci Wuhan 430048 Peoples R China Zhongnan Univ Econ & Law Sch Math & Stat Wuhan 430073 Peoples R China

ISBN: (数字)9781665470452

ISBN: (纸本)9781665470469;9781665470452

To improve the performance of the harmony search algorithm and enable the processing of increasingly complicated optimization problems, a global harmony search algorithm based on tent chaos map and elite reverse learning (HS-TE) has been proposed. The algorithm uses the tent chaos map to initialize the population and adopts the elite reverse learning strategy to optimize the iterative process. The method reduces the algorithm's dependence on the initial solution, improves the search optimization ability, enhances the diversity of the population, and establishes adaptive parameters to control the development and exploration of the iterative process, which is beneficial to improving the algorithm's search ability. Create test experiments: Various HS algorithms perform classic benchmark function tests. The experimental test data shows that the algorithm is better than the current five improved harmony search algorithms and has better convergence and accuracy. The algorithm is used to improve the penalty parameters and kernel function parameters of SVR, and then use the optimized SVR to perform regression prediction on the daily opening number of the Shanghai Stock Exchange. According to the experimental results, the upgraded SVR provides better prediction performance. It works both in theory and in real life and can be used to predict the Shanghai Securities Composite Index.

关键词： harmony search algorithm elite reverse learning tent chaos map adaptive parameters svr

来源：评论

学校读者我要写书评

暂无评论

A dual population collaborative harmony search algorithm with adaptive population size for the system reliability-redundancy allocation problems

引用

JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 2024年第2期11卷 285-313页

作者： Ouyang, Haibin Liang, Siqi Li, Steven Zhou, Ziyu Zhan, Zhi-Hui Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China RMIT Univ Grad Sch Business & Law Melbourne 3000 Australia South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China

Aiming at the problem that the diversity of the current double population algorithm with dynamic population size reduction cannot be guaranteed in real time in iteration and is easy to fall into local optimum, this study presents a dual population collaborative harmony search algorithm with adaptive population size (DPCHS). Firstly, we propose a dual population algorithm framework for improving the algorithm global search capability. Within this framework, the guidance selection strategy and information interaction mechanism are integrated to strengthen the competition and cooperation among populations, and achieving a good balance between exploration and exploitation. A population state assessment method is designed to monitor population changes in real-time for enhancing population real-time self-regulation. Additionally, population size adjustment approach is designed to adopted to effectively streamline population resources and improve population quality. Comprehensive experiment results demonstrate that DPCHS effectively addresses system reliability-redundancy allocation problems with superior performance and robust convergence compared with other HS variants and algorithms from different categories. Graphical Abstract

关键词： harmony search algorithm population state assessment population size adaptation system reliability

来源：评论

学校读者我要写书评

暂无评论

harmony search algorithm for Patient Admission Scheduling Problem

引用

JOURNAL OF INTELLIGENT SYSTEMS 2020年第1期29卷 540-553页

作者： Abu Doush, Iyad Al-Betar, Mohammed Azmi Awadallah, Mohammed A. Hammouri, Abdelaziz, I Al-Khatib, Ra'ed M. AlMustafa, Siba Alkhraisat, Habes Amer Univ Kuwait Comp Sci & Informat Syst Dept Salmiya Kuwait Yarmouk Univ Comp Sci Dept Irbid Jordan Al Balqa Appl Univ Al Huson Univ Coll Dept Informat Technol Irbid Jordan Al Aqsa Univ Dept Comp Sci POB 4051 Gaza Palestine Al Balqa Appl Univ Dept Comp Informat Syst Al Salt Jordan

The patient admission scheduling (PAS) problem is an optimization problem in which we assign patients automatically to beds for a specific period of time while preserving their medical requirements and their preferences. In this paper, we present a novel solution to the PAS problem using the harmony search (HS) algorithm. We tailor the HS to solve the PAS problem by distributing patients to beds randomly in the harmony memory (HM) while respecting all hard constraints. The proposed algorithm uses five neighborhood strategies in the pitch adjustment stage. This technique helps in increasing the variations of the generated solutions by exploring more solutions in the search space. The PAS standard benchmark datasets are used in the evaluation. Initially, a sensitivity analysis of the HS algorithm is studied to show the effect of its control parameters on the HS performance. The proposed method is also compared with nine methods: non-linear great deluge (NLGD), simulated annealing with hyper-heuristic (HH-SA), improved with equal hyperheuristic (HH-IE), simulated annealing (SA), tabu search (TS), simple random simulated annealing with dynamic heuristic (DHS-SA), simple random improvement with dynamic heuristic (DHS-OI), simple random great deluge with dynamic heuristic (DHS-GD), and biogeography-based optimization (BBO). The proposed HS algorithm is able to produce comparably competitive results when compared with these methods. This proves that the proposed HS is a very efficient alternative to the PAS problem, which can be efficiently used to solve many scheduling problems of a large-scale data.

关键词： harmony search algorithm optimization patient admission problem metaheuristic patient scheduling problem

来源：评论

学校读者我要写书评

暂无评论

Solving Multi-Objective Two-Sided Assembly Line Balancing Problems by harmony search algorithm Based on Pareto Entropy

引用

IEEE ACCESS 2021年 9卷 121728-121742页

作者： Zheng, Xiaojun Ning, Shiduo Sun, Hao Zhong, Jiang Tong, Xiaoying Dalian Jiaotong Univ Sch Mech Engn Dalian 116028 Peoples R China

Two-sided assembly lines are designed to produce large and complex products, where workers can perform on both sides at the same time. This paper establishes a mathematical model for the multi-objective two-sided assembly line balancing problems with additional constraints (MOATALBP). The model considers both workers skills and the balance of the assembly line, aiming to maximize efficiency and minimize workers cost and smoothness index. A harmony search algorithm (HS) based on Pareto entropy (PE-MHS) is proposed to solve MOATALBP. The difference entropy of Pareto solutions is employed to adjust the algorithm parameters to enhance the optimization ability of PE-MHS. Moreover, a fine-tuning operation combining insertion and inverse sequence is utilized to avoid the algorithm from falling into local optima. Ultimately, non-dominated sorting ensures a set of well-distributed Pareto solutions. The experimental results of different problems indicate that the proposed algorithm can achieve better solutions than three classical algorithms (NSGAII, SPEA2 and HS) for the MOATALBP.

关键词： Task analysis search problems Entropy Mathematical model Indexes Genetic algorithms Sorting harmony search algorithm multi-objective optimization Pareto entropy two-sided assembly line balancing

来源：评论

学校读者我要写书评

暂无评论

An application for solving minimization problems using the harmony search algorithm

引用

SOFTWAREX 2024年 27卷

作者： Makhmudov, Fazliddin Kilichev, Dusmurod Cho, Young Im Gachon Univ Dept Comp Engn Seongnam South Korea

The harmony search (HS) algorithm, inspired by the improvisational process of musicians, offers a novel and effective approach to optimization problems. This paper presents an application designed to solve a wide range of minimization problems using the HS algorithm. By simulating the creative exploration and refinement seen in musical harmonies, the HS algorithm efficiently navigates complex solution landscapes, delivering high accuracy and computational efficiency. Illustrated through various optimization examples, this tool showcases the versatility and power of the HS algorithm in addressing linear, non-linear, and discrete models. Our work highlights the practical utility of bio-inspired algorithms in solving real -world problems, providing a userfriendly platform for researchers and engineers to harness the potential of the HS algorithm in diverse fields.

关键词： harmony search algorithm Minimization problem

来源：评论

学校读者我要写书评

暂无评论

Feasibility study for size optimisation of a geothermal/PV/wind/diesel hybrid power plant using the harmony search algorithm

引用

INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY 2021年第6期40卷 584-601页

作者： Naseh, Majid Reza Behdani, Emad Islamic Azad Univ Birjand Branch Dept Elect Engn Birjand Iran

Using hybrid renewable energy systems is a smart choice for reducing the carbon emitted by power plants. It also helps climate change mitigation and global warming, leading to universal health for humans and the environment. The efficiency of these systems depends on choosing the right combination of renewable sources, their sizes, and proper scheduling of the generating units. This paper suggests an optimisation method for sizing a geothermal/PV/wind/diesel system, both in off-grid and grid-connected configurations. In the grid-connected mode, the possibility of selling surplus energy generated by renewable resources to the network is considered. Investigations reveal that without accurate control of geothermal reservoirs, they may become depleted. In this study, a strategy is suggested for unit commitment;moreover, the harmony search algorithm is used to find the optimal size of the hybrid system in both configurations. The effectiveness of the proposed approach is represented by simulating an HRES for Ferdows/Iran.

关键词： hybrid renewable energy system harmony search algorithm geothermal power plant control strategy optimization

来源：评论

学校读者我要写书评

暂无评论

Adaptive harmony search algorithm utilizing differential evolution and opposition-based learning

引用

MATHEMATICAL BIOSCIENCES AND ENGINEERING 2021年第4期18卷 4226-4246页

作者： Kang, Di-Wen Mo, Li-Ping Wang, Fang-Ling Ou, Yun Jishou Univ Coll Informat Sci & Engn Jishou 416000 Peoples R China

An adaptive harmony search algorithm utilizing differential evolution and opposition based learning (AHS-DE-OBL) is proposed to overcome the drawbacks of the harmony search (HS) algorithm, such as its low fine-tuning ability, slow convergence speed, and easily falling into a local optimum. In AHS-DE-OBL, three main innovative strategies are adopted. First, inspired by the differential evolution algorithm, the differential harmonies in the population are used to randomly perturb individuals to improve the fine-tuning ability. Then, the search domain is adaptively adjusted to accelerate the algorithm convergence. Finally, an opposition-based learning strategy is introduced to prevent the algorithm from falling into a local optimum. The experimental results show that the proposed algorithm has a better global search ability and faster convergence speed than other selected improved harmony search algorithms and selected metaheuristic approaches.

关键词： harmony search algorithm differential evolution opposition-based learning adaptive adjustment strategy optimization

来源：评论

学校读者我要写书评

暂无评论

Multilevel thresholding image segmentation based on energy curve with harmony search algorithm

引用

AIN SHAMS ENGINEERING JOURNAL 2021年第1期12卷 1-20页

作者： Srikanth, R. Bikshalu, K. Kakatiya Inst Technol & Sci Dept ECE Warangal Telangana India Kakatiya Univ Dept ECE Warangal Telangana India

Image segmentation is a process of portion image into regions. From image segmentation schemes available, multilevel thresholding on the histogram is a highly established method. Otsu's method is a significant multilevel thresholding technique, in this multiple threshold levels selected on histogram and group the pixels of an image into different regions. The optimized threshold levels computed with an Optimized technique by maximizing the inter-class variance. Methods with histograms are incapable to possess spatial details of contextual information for finding optimal threshold levels. As a remedy, a novel method proposed the Energy Curve is used instead of a histogram with Otsu's method and harmony search algorithm to compute optimized gray levels. The proposed method experimented on several benchmark images, and results compared with various optimization algorithms with histogram by Dunn Index, DB Index, SD Index, mean of fitness and PSNR, comparison clarifies that the proposed method is superior to histogram-based methods. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Image segmentation Otsu method Multilevel thresholding Energy curve harmony search algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：