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Optimal Network Reconfiguration of Large-Scale Distribution System Using harmony search algorithm

IEEE TRANSACTIONS ON POWER SYSTEMS 2011年第3期26卷 1080-1088页

作者： Rao, Rayapudi Srinivasa Narasimham, Sadhu Venkata Lakshmi Raju, Manyala Ramalinga Rao, A. Srinivasa JNT Univ Dept Elect & Elect Engn Kakinada India JNT Univ Sch Informat Technol Hyderabad Andhra Pradesh India GITAM Univ Dept Elect & Elect Engn Vishakapatnam India

Electrical distribution network reconfiguration is a complex combinatorial optimization process aimed at finding a radial operating structure that minimizes the system power loss while satisfying operating constraints. In this paper, a harmony search algorithm (HSA) is proposed to solve the network reconfiguration problem to get optimal switching combination in the network which results in minimum loss. The HSA is a recently developed algorithm which is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search which eliminates the need for derivative information. Simulations are carried out on 33- and 119-bus systems in order to validate the proposed algorithm. The results are compared with other approaches available in the literature. It is observed that the proposed method performed well compared to the other methods in terms of the quality of solution.

关键词： Distribution system harmony search algorithm loss reduction network reconfiguration

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Multi-product multi-chance-constraint stochastic inventory control problem with dynamic demand and partial back-ordering: A harmony search algorithm

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JOURNAL OF MANUFACTURING SYSTEMS 2012年第2期31卷 204-213页

作者： Taleizadeh, Ata Allah Niaki, Seyed Taghi Akhavan Seyedjavadi, Seyed Mohammad Haji Sharif Univ Technol Dept Ind Engn Tehran *** Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Islamic Azad Univ Dept Comp Engn Qazvin Iran

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms. (C) 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： Inventory control Multi-product multi-constraint Dynamic demand Stochastic replenishment Partial back-ordering harmony search algorithm

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Optimization of multi-pass face-milling via harmony search algorithm

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JOURNAL OF MATERIALS PROCESSING TECHNOLOGY 2009年第5期209卷 2386-2392页

作者： Zarei, O. Fesanghary, M. Farshi, B. Saffar, R. Jalili Razfar, M. R. IUST Dept Mech Engn Tehran *** Iran Amir Kabir Univ Technol Dept Mech Engn Tehran 158754413 Iran

This study presents a harmony search (HS) algorithm to determine the optimum cutting parameters for multi-pass face-milling. The optimum value of machining parameters including number of passes, depth of cut in each pass, speed and feed is obtained to minimize total production cost while considering technological constraints such as allowable speed, feed, surface finish, tool life and machine tool capabilities. An illustrative example is used to demonstrate the ability of the HS algorithm and for validation purpose, the genetic algorithm (GA) is used to solve the same problem. Comparison of the results reveals that the HS algorithm converges to optimum solution with higher accuracy in comparison with GA. (c) 2008 Elsevier B.V All rights reserved.

关键词： Face-milling Optimization harmony search algorithm Genetic algorithm

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Network decomposition using Kernighan-Lin strategy aided harmony search algorithm

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SWARM AND EVOLUTIONARY COMPUTATION 2012年 7卷 1-6页

作者： Ezhilarasi, G. A. Swarup, K. S. Indian Inst Technol Dept Elect Engn Madras 600036 Tamil Nadu India

Power system is a large-scale network with a number of components and interconnections for which centralized control becomes cumbersome. For multi-area computations, decentralization is necessary. For implementation of this approach network decomposition becomes an essential task. In this paper the network decomposition problem is solved as an optimization problem using the harmony search (HS) algorithm. To improve the performance of the HS algorithm, a widely used graph bi-partitioning method called Kernighan-Lin (KL) strategy is used in the improvisation process. KL strategy is used in the partitioning of digital and VLSI circuits and is suitable for bi-partitioning networks. The connectivity of the partitioned clusters are checked by means of graph traversal techniques. Simulation are carried out on IEEE Standard systems and found to be very effective in decomposition of the system hierarchically. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Network decomposition Distributed computing harmony search algorithm Kernighan-Lin algorithm

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An almost-parameter-free harmony search algorithm for groundwater pollution source identification

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WATER SCIENCE AND TECHNOLOGY 2013年第11期68卷 2359-2366页

作者： Jiang, Simin Zhang, Yali Wang, Pei Zheng, Maohui Tongji Univ Dept Hydraul Engn Shanghai 200092 Peoples R China Changzhou Acad Environm Sci Changzhou 213022 Peoples R China Tongji Univ Inst Disaster Prevent & Relief Shanghai 200092 Peoples R China

The spatiotemporal characterization of unknown sources of groundwater pollution is frequently encountered in environmental problems. This study adopts a simulation-optimization approach that combines a contaminant transport simulation model with a heuristic harmony search algorithm to identify unknown pollution sources. In the proposed methodology, an almost-parameter-free harmony search algorithm is developed. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem, and the identified results indicate that the proposed almost-parameter-free harmony search algorithm-based optimization model can give satisfactory estimations, even when the irregular geometry, erroneous monitoring data, and prior information shortage of potential locations are considered.

关键词： groundwater harmony search algorithm pollution source identification simulation-optimization approach

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On the iterative convergence of harmony search algorithm and a proposed modification

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APPLIED MATHEMATICS AND COMPUTATION 2014年 247卷 1064-1095页

作者： Yang, Hai-bin Ou Gao, Li-qun Li, Steven Kong, Xiangyong Zou, De-xuan Northeastern Univ Coll Informat Sci & Engn Shenyang 110004 Peoples R China RMIT Univ Grad Sch Business & Law Melbourne Vic 3000 Australia Jiangsu Normal Univ Sch Elect Engn & Automat Xuzhou 221116 Peoples R China

Inspired by the improvisation process of music players, a population-based meta-heuristic algorithm-harmony search (HS) has been proposed recently. HS is good at exploitation, but it can be poor at exploration, and its convergence performance can also be an issue in some cases. To address these disadvantages, the distance bandwidth (bw) adjusting methods proposed in recent literatures are summarized and the exploration ability of HS improvisation is investigated in this paper. Further, the relationship between improvisation exploration and each parameter under asymmetric interval is derived, and an iterative convergence sufficiency of the iteration equation which consists of variance expectation and mean expectation is proven theoretically. Based on these analyses, a modified harmony search (MHS) algorithm is proposed. Moreover, the effects of the key parameters including HMS, PAR and HMCR on the performance of the MHS algorithm are discussed in depth. Experimental results reveal that the proposed MHS algorithm performs better than HS as well as its state-of-the-art variants and other classic excellent meta-heuristic approaches. (C) 2014 Elsevier Inc. All rights reserved.

关键词： harmony search algorithm Exploitation Bandwidth Exploration ability Iterative convergence

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A multi-objective grouping harmony search algorithm for the optimal distribution of 24-hour medical emergency units

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EXPERT SYSTEMS WITH APPLICATIONS 2013年第6期40卷 2343-2349页

作者： Landa-Torres, I. Manjarres, D. Salcedo-Sanz, S. Del Ser, J. Gil-Lopez, S. TECNALIA RES & INNOVAT OPTIMA Area Zamudio 48170 Bizkaia Spain Univ Alcala de Henares Dept Signal Theory & Commun Madrid 28871 Spain

This paper presents a novel multi-objective heuristic approach for the efficient distribution of 24-h emergency units. This paradigm is essentially a facility location problem that involves determining the optimum locations, within the existing health care centers, where to deploy 24-h emergency resources, as well as an efficient assignment of patients to such newly placed resources through the existing medical care infrastructure. The formulation of the underlying NP-complete problem is based on a bi-objective distance and cost metric, which is tackled in our approach by combining a harmony search algorithm with a grouping encoding and a non-dominated solution sorting strategy. Additionally, the nominal grouping encoding procedure has been redefined in order to reduce the dimension of the search space, thus allowing for a higher efficiency of the searching process. Extensive simulations in a real scenario - based on the geographic location of medical centers over the provinces of Guadalajara and Cuenca (Spain) - show that the proposed algorithm is statistically robust and provides a wide range of feasible solutions, hence offering multiple alternatives for the distribution of emergency units. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： harmony search algorithm Multi-objective optimization Grouping-based encoding Health-care facility location problem

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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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An improved variant of the conventional harmony search algorithm

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APPLIED MATHEMATICS AND COMPUTATION 2014年 227卷 821-830页

作者： Contreras, Jhonatan Amaya, Ivan Correa, Rodrigo Univ Ind Santander Sch Elect Elect & Telecommun Engn Bucaramanga Colombia

The harmony search algorithm (HS) has been used for optimization in different fields, and despite the relative short time it has been around, it already has many variants. This article presents a new modification of HS, based on variable parameters, which is able to yield better results than previously reported data, and with the additional benefit of not requiring prior knowledge of the maximum number of iterations. In this research, a comparison is made with the original HS algorithm, and with its improved version (i.e. IHS), finding that the proposed variants not only reduce convergence time of the algorithm, but they also increase its precision. Some commonly used benchmark functions were used as a testing scenario, and the performance of the novel approach is evaluated for an objective function in up to 1000D, where it was found to converge appropriately. These findings are important since they indicate that the proposed version could be used for different kinds of optimization problems, thus allowing a broader use of the HS algorithm. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Global optimization harmony search algorithm Metaheuristics Optimization Standard test functions

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Equilibrium optimizer-based harmony search algorithm with nonlinear dynamic domains and its application to real-world optimization problems

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ARTIFICIAL INTELLIGENCE REVIEW 2024年第7期57卷 166-166页

作者： Wang, Jinglin Ouyang, Haibin Li, Steven Ding, Weiping Gao, Liqun Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou Peoples R China RMIT Univ Grad Sch Business & Law Melbourne 3000 Australia Nantong Univ Sch Informat Sci & Technol Nantong 226019 Peoples R China

harmony search (HS) algorithm is a swarm intelligence algorithm inspired by musical improvisation. Although HS has been applied to various engineering problems, it faces challenges such as getting trapped in local optima, slow convergence speed, and low optimization accuracy when applied to complex problems. To address these issues, this paper proposes an improved version of HS called Equilibrium Optimization-based harmony search algorithm with Nonlinear Dynamic Domains (EO-HS-NDD). EO-HS-NDD integrates multiple leadership-guided strategies from the Equilibrium Optimizer (EO) algorithm, using harmony memory considering disharmony and historical harmony memory, while leveraging the hidden guidance direction information from the Equilibrium Optimizer. Additionally, the algorithm designs a nonlinear dynamic convergence domain to adaptively adjust the search space size and accelerate convergence speed. Furthermore, to balance exploration and exploitation capabilities, appropriate adaptive adjustments are made to harmony Memory Considering Rate (HMCR) and Pitch Adjustment Rate (PAR). Experimental validation on the CEC2017 test function set demonstrates that EO-HS-NDD outperforms HS and nine other HS variants in terms of robustness, convergence speed, and optimization accuracy. Comparisons with advanced versions of the Differential Evolution (DE) algorithm also indicate that EO-HS-NDD exhibits superior solving capabilities. Moreover, EO-HS-NDD is applied to solve 15 real-world optimization problems from CEC2020 and compared with advanced algorithms from the CEC2020 competition. The experimental results show that EO-HS-NDD performs well in solving real-world optimization problems.

关键词： harmony search algorithm Equilibrium optimizer Dynamic domains Optimization Meta-heuristic algorithms

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