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Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling

INFORMATION SCIENCES 2014年第1期289卷 76-90页

作者： Gao, K. Z. Suganthan, P. N. Pan, Q. K. Chua, T. J. Cai, T. X. Chong, C. S. Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Liaocheng Univ Comp Sch Liaocheng 252000 Peoples R China Singapore Inst Mfg Technol Singapore 638075 Singapore

This paper proposes a Pareto-based grouping discrete harmony search algorithm (PGDHS) to solve the multi-objective flexible job shop scheduling problem (FJSP). Two objectives, namely the maximum completion time (makespan) and the mean of earliness and tardiness, are considered simultaneously. Firstly, two novel heuristics and several existing heuristics are employed to initialize the harmony memory. Secondly, multiple harmony generation strategies are proposed to improve the performance of harmony search algorithm. The operation sequence in a new harmony is produced based on the encoding method and the characteristics of FJSP. Thirdly, two local search methods based on critical path and due date are embedded to enhance the exploitation capability. Finally, extensive computational experiments are carried out using well-known benchmark instances. Three widely used performance measures, number of non-dominated solutions, diversification metric and quality metric, are employed to test the performance of PGDHS algorithm. Computational results and comparisons show the efficiency and effectiveness of the proposed PGDHS algorithm for solving multi-objective flexible job-shop scheduling problem. (C) 2014 Published by Elsevier Inc.

关键词： Flexible job shop scheduling harmony search algorithm Multi-objective optimization Local search

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Hybridizing harmony search algorithm with different mutation operators for continuous problems

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APPLIED MATHEMATICS AND COMPUTATION 2014年 232卷 1166-1182页

作者： Hasan, Basima Hani F. Abu Doush, Iyad Al Maghayreh, Es Lam Alkhateeb, Faisal Hamdan, Mohammad Yarmouk Univ Dept Comp Sci Irbid 21163 Jordan

harmony search (HS) is a recent EA inspired by musical improvisation process to seek a pleasing harmony. Mutation is a vital component used in Evolutionary algorithms (EA) where a value in the population is randomly selected to be altered to improve the evolution process. The original HS algorithm applies an operation similar to mutation during the random consideration operator. During random selection operator a value within the range of the decision variable is selected randomly to explore different areas in the search space. This paper aims at experimentally evaluating the performance of HS algorithm after replacing the random consideration operator in the original HS with five different mutation methods. The different variations of HS are experimented on standard benchmark functions in terms of final obtained solution and convergence speed. The results show that using polynomial mutation improves the performance of the HS algorithm for most of the used functions. (C) 2013 Elsevier Inc. All rights reserved.

关键词： harmony search algorithm Evolutionary algorithms Mutation Meta-heuristic algorithm Polynomial mutation

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Hybrid parallel chaos optimization algorithm with harmony search algorithm

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APPLIED SOFT COMPUTING 2014年第0期17卷 12-22页

作者： Yuan, Xiaofang Zhao, Jingyi Yang, Yimin Wang, Yaonan Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China

The application of chaotic sequences can be an interesting alternative to provide search diversity in an optimization procedure, named chaos optimization algorithm (COA). Since the chaotic motion is pseudorandomness and chaotic sequences are sensitive to the initial conditions, the search ability of COA is usually effected by the starting values. Considering this weakness, parallel chaos optimization algorithm( PCOA) is studied in this paper. To obtain optimum solution accurately, harmony search algorithm (HSA) is integrated with PCOA to form a novel hybrid algorithm. Different chaotic maps are compared and the impacts of parallel parameter on the hybrid algorithm are discussed. Several simulation results are used to show the effective performance of the proposed hybrid algorithm. (C) 2013 Elsevier B. V. All rights reserved.

关键词： Chaos optimization algorithm (COA) Parallel chaos optimization algorithm (PCOA) harmony search algorithm Hybrid algorithm Chaotic map

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Modularity-Based Graph Clustering using harmony search algorithm

Modularity-Based Graph Clustering using Harmony Search Algor...

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International Conference on Advanced Computer Science Applications and Technologies

作者： Yilmaz ATAY Halife KODAZ Department of Computer Engineering Selcuk University

ISBN: (纸本)9781509004256

Real-world networks contain variety of meaningful information inside them that can be revealed. These networks can be biological, social, ecological and technological networks. Each of these contains specific information about their field. This information cannot be obtained with simple techniques. Various techniques and algorithms have been developed to uncover useful information from complex relationships inside the network. In this paper, to divide graphs according to modularity measure to subgraphs harmony search algorithm is used which is inspired by music improvisation. This algorithm has been tested with 5 different real-world networks. The obtained quantitative values for each network have been given in the tables. In addition the proposed algorithm, has achieved the best known modularity measure of Zachary's Karate Club network which is commonly used in the literature and the latest subsets generated according to this modularity measure has been given at the end of section V. According to the results obtained from experiments it has been observed that HM algorithm gives faster results on solution of problem addressed in this study than most algorithms like genetic algorithm and bat algorithm. However, the proposed algorithm requires a larger size of harmony memory and more number of iterations for maximum modularity values.

关键词： Community mining Complex systems Graph clustering harmony search algorithm Modularity Real networks

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Best Polynomial harmony search with Best β-Hill Climbing algorithm

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JOURNAL OF INTELLIGENT SYSTEMS 2021年第1期30卷 1-17页

作者： Abu Doush, Iyad Santos, Eugene Yarmouk Univ Dept Comp Sci Irbid Jordan Amer Univ Kuwait Dept Comp Sci Dept & Informat Syst Salmiya Kuwait Dartmouth Coll Thayer Sch Engn 8000 Cummings Hall Hanover NH 03755 USA

harmony search algorithm (HSA) is an evolutionary algorithm which mimics the process of music improvisation to obtain a nice harmony. The algorithm has been successfully applied to solve optimization problems in different domains. A significant shortcoming of the algorithm is inadequate exploitation when trying to solve complex problems. The algorithm relies on three operators for performing improvisation: memory consideration, pitch adjustment, and random consideration. In order to improve algorithm efficiency, we use roulette wheel and tournament selection in memory consideration, replace the pitch adjustment and random consideration with a modified polynomial mutation, and enhance the obtained new harmony with a modified beta-hill climbing algorithm. Such modification can help to maintain the diversity and enhance the convergence speed of the modified HS algorithm. beta-hill climbing is a recently introduced local search algorithm that is able to effectively solve different optimization problems. beta-hill climbing is utilized in the modified HS algorithm as a local search technique to improve the generated solution by HS. Two algorithms are proposed: the first one is called PHS beta-HC and the second one is called Imp. PHS beta-HC. The two algorithms are evaluated using 13 global optimization classical benchmark function with various ranges and complexities. The proposed algorithms are compared against five other HSA using the same test functions. Using Friedman test, the two proposed algorithms ranked 2nd (Imp. PHS beta-HC) and 3rd (PHS beta-HC). Furthermore, the two proposed algorithms are compared against four versions of particle swarm optimization (PSO). The results show that the proposed PHS beta-HC algorithm generates the best results for three test functions. In addition, the proposed Imp. PHS beta-HC algorithm is able to overcome the other algorithms for two test functions. Finally, the two proposed algorithms are compared with four variations of differ

关键词： harmony search algorithm Evolutionary algorithms Hill Climbing Polynomial Mutation beta-Hill Climbing

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Music genre classification based on local feature selection using a self-adaptive harmony search algorithm

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DATA & KNOWLEDGE ENGINEERING 2014年第Jul.期92卷 60-76页

作者： Huang, Yin-Fu Lin, Sheng-Min Wu, Huan-Yu Li, Yu-Siou Natl Yunlin Univ Sci & Technol Dept Comp Sci & Informat Engn Touliu 640 Yunlin Taiwan

This paper proposes an automatic music genre-classification system based on a local feature-selection strategy by using a self-adaptive harmony search (SAHS) algorithm. First, five acoustic characteristics (i.e., intensity, pitch, timbre, tonality, and rhythm) are extracted to generate an original feature set. A feature-selection model using the SAHS algorithm is then employed for each pair of genres, thereby deriving the corresponding local feature set. Finally, each one-against-one support vector machine (SVM) classifier is fed with the corresponding local feature set, and the majority voting method is used to classify each musical recording. Experiments on the GTZAN dataset were conducted, demonstrating that our method is effective. The results show that the local-selection strategies using wrapper and filter approaches ranked first and third in performance among all relevant methods. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Classification Information retrieval Feature selection harmony search algorithm

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A multi-population harmony search algorithm with external archive for dynamic optimization problems

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INFORMATION SCIENCES 2014年 272卷 84-95页

作者： Turky, Ayad Mashaan Abdullah, Salwani Univ Kebangsaan Malaysia Ctr Artificial Intelligence Technol Data Min & Optimisat Res Grp Bangi 43600 Selangor Malaysia Swinburne Univ Technol Fac Informat & Commun Technol Hawthorn Vic 3122 Australia

Dynamic optimization problems present great challenges to the research community because their parameters are either revealed or changed during the course of an ongoing optimization process. These problems are more challenging than static problems in real-world applications because the latter are usually dynamic, with the environment constantly subjected to change or the size of a problem increasing sporadically. In solving dynamic optimization problems in the real world, proposed solutions should be able to monitor the movement of the optimal point and the changes in the landscape solutions. In this paper, a multi-population harmony search algorithm with external archive for dynamic optimization problems is proposed. harmony search algorithm is a population-based meta-heuristic optimization technique that is similar to a musical process when a musician is attempting to find a state of harmony. To tackle the problem of dynamism, the population of solutions is divided into several sub-populations such that each sub-population takes charge exploring or exploiting the search space. To enhance the algorithm performance further, an external archive is used to save the best solutions for later use. These solutions will then be used to replace redundant solutions in the harmony memory. The proposed algorithm is tested on the Moving Peak Benchmark. Empirical results show that the proposed algorithm produces better results than several of the current state-of-the-art algorithms. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Multi-population harmony search algorithm Dynamic optimization problems External archive

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Variance-Based harmony search algorithm for Unimodal and Multimodal Optimization Problems with Application to Clustering

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CYBERNETICS AND SYSTEMS 2014年第6期45卷 486-511页

作者： Kumar, Vijay Chhabra, Jitender Kumar Kumar, Dinesh JCDMCOE Comp Sci & Engn Dept Sirsa Haryana India Natl Inst Technol Dept Comp Engn Kurukshetra Haryana India GJUS&T Dept Comp Sci & Engn Hisar Haryana India

This article presents a novel variance-based harmony search algorithm (VHS) for solving optimization problems. VHS incorporates the concepts borrowed from the invasive weed optimization technique to improve the performance of the harmony search algorithm (HS). This eliminates the main problem of constant parameter setting in the algorithm proposed recently and named as explorative HS. It uses the variance of a current population as well as presents a solution vector to improvise the harmony memory. In addition, the dynamic pitch adjustment operator is used to avoid solution oscillation. The proposed algorithm is evaluated on 14 standard benchmark functions of various characteristics. The performance of the proposed algorithm is investigated and compared with classical HS, an improved version of HS, the global best HS, self-adaptive HS, explorative HS, and the recently proposed state-of-art gravitational search algorithm. Experimental results reveal that the proposed algorithm outperforms the above-mentioned approaches. The effects of scalability, noise, harmony memory size, and harmony memory consideration rate have also been investigated with the proposed algorithm. The proposed algorithm is then employed for a data clustering problem. Four real-life datasets selected from the UCI machine learning repository have been used. The results indicate that the VHS-based clustering outperforms the existing well-known clustering algorithms.

关键词： harmony search algorithm metaheuristics optimization

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Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems

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JOURNAL OF COMPUTATIONAL SCIENCE 2014年第2期5卷 144-155页

作者： Kumar, Vijay Chhabra, Jitender Kumar Kumar, Dinesh JCDM Coll Engn CSE Dept Sirsa Haryana India Natl Inst Technol Dept Comp Engn Kurukshetra Haryana India GJUS&T Dept Comp Sci & Engn Hisar Haryana India

This paper presents a parameter adaptive harmony search algorithm (PAHS) for solving optimization problems. The two important parameters of harmony search algorithm namely harmony Memory Consideration Rate (HMCR) and Pitch Adjusting Rate (PAR), which were either kept constant or the PAR value was dynamically changed while still keeping HMCR fixed, as observed from literature, are both being allowed to change dynamically in this proposed PAHS. This change in the parameters has been done to get the global optimal solution. Four different cases of linear and exponential changes have been explored. The change has been allowed during the process of improvization. The proposed algorithm is evaluated on 15 standard benchmark functions of various characteristics. Its performance is investigated and compared with three existing harmony search algorithms. Experimental results reveal that proposed algorithm outperforms the existing approaches when applied to 15 benchmark functions. The effects of scalability, noise, and harmony memory size have also been investigated on four approaches of HS. The proposed algorithm is also employed for data clustering. Five real life datasets selected from UCI machine learning repository are used. The results show that, for data clustering, the proposed algorithm achieved results better than other algorithms. (C) 2013 Elsevier B.V. All rights reserved.

关键词： harmony search algorithm Optimization Metaheuristic Benchmark problems Data clustering

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Improving a model for the dynamic modulus of asphalt using the modified harmony search algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2014年第8期41卷 3856-3860页

作者： Lee, Sangyum Mun, Sungho Seoul Metropolitan Govt Rd Management Div Seoul South Korea Seoul Natl Univ Sci & Technol Dept Civil Engn Seoul South Korea

We report the improvement of a dynamic modulus model using a modified harmony search (MHS) algorithm to describe the resistance to rutting and fatigue cracking of asphalt concrete mixtures. The MHS algorithm was reformulated to improve the harmony search (HS) algorithm by introducing minimum and maximum bandwidths. Using the MHS algorithm, model parameters for lime-modified asphalt concrete mixtures were extracted and a good fit to the dynamic modulus data obtained from laboratory tests was achieved. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： harmony search algorithm Modified harmony search algorithm Asphalt concrete mixture Dynamic modulus

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