A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications

Abualigah, Laith; Diabat, Ali; Geem, Zong Woo

doi:10.3390/app10113827

Cited by 112 publications

(41 citation statements)

References 98 publications

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“…e proposed approach has less execution time than the other techniques. A survey on clustering techniques using harmony search algorithms was found in [129].…”

Section: Electrical Engineeringmentioning

confidence: 99%

A Systematic Review on Harmony Search Algorithm: Theory, Literature, and Applications

Dubey

Kumar

Kaur

et al. 2021

Mathematical Problems in Engineering

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Harmony search algorithm is the recently developed metaheuristic in the last decade. It mimics the behavior of a musician producing a perfect harmony. It has been used to solve the wide variety of real-life optimization problems due to its easy implementation over other metaheuristics. It has an ability to provide the balance between exploration and exploitation during search. In this paper, a systematic review on harmony search algorithm (HSA) is presented. The natural inspiration and conceptual framework of HSA are discussed. The control parameters of HSA are described with their mathematical foundation. The improvement and hybridization in HSA with other metaheuristics are discussed in detail. The applicability of HSA in different problem domains is studied. The future research directions of HSA are also investigated.

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“…e proposed approach has less execution time than the other techniques. A survey on clustering techniques using harmony search algorithms was found in [129].…”

Section: Electrical Engineeringmentioning

confidence: 99%

A Systematic Review on Harmony Search Algorithm: Theory, Literature, and Applications

Dubey

Kumar

Kaur

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…The main advantages of the HSA are clarity of execution, record of success, and ability to tackle several complex problems (e.g., power systems, job scheduling, congestion management) [16][17][18]. Another reason for its success and reputation is that the HSA can make trade-offs between convergent and divergent regions.…”

Section: Cmentioning

confidence: 99%

HASPO: Harmony Search-Based Parameter Optimization for Just-in-Time Software Defect Prediction in Maritime Software

et al. 2021

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Software is playing the most important role in recent vehicle innovations, and consequently the amount of software has rapidly grown in recent decades. The safety-critical nature of ships, one sort of vehicle, makes software quality assurance (SQA) a fundamental prerequisite. Just-in-time software defect prediction (JIT-SDP) aims to conduct software defect prediction (SDP) on commit-level code changes to achieve effective SQA resource allocation. The first case study of SDP in the maritime domain reported feasible prediction performance. However, we still consider that the prediction model has room for improvement since the parameters of the model are not optimized yet. Harmony search (HS) is a widely used music-inspired meta-heuristic optimization algorithm. In this article, we demonstrated that JIT-SDP can produce better performance of prediction by applying HS-based parameter optimization with balanced fitness value. Using two real-world datasets from the maritime software project, we obtained an optimized model that meets the performance criterion beyond the baseline of a previous case study throughout various defect to non-defect class imbalance ratio of datasets. Experiments with open source software also showed better recall for all datasets despite the fact that we considered balance as a performance index. HS-based parameter optimized JIT-SDP can be applied to the maritime domain software with a high class imbalance ratio. Finally, we expect that our research can be extended to improve the performance of JIT-SDP not only in maritime domain software but also in open source software.

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“…k ‐means algorithm is a greedy algorithm which generally converges to the local minimum except for cases where the clusters are well separated. An efficient mechanism to perform text clustering using heuristic techniques were presented by References 29‐31. A frequent and rare itemset mining approach to transaction clustering was presented by Tummala et al 32 Various optimization algorithms using heuristic methods were given in References 33‐35.…”

Section: Related Workmentioning

confidence: 99%

An efficient and novel data clustering and run length encoding approach to image compression

Oswald

Haritha

Raja

et al. 2021

Concurrency and Computation

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The paper explores the domain of lossy compression, specifically incorporating data mining techniques in the process of image encoding. Clustering is employed to group similar pixels in the image and henceforth use cluster labels in compressing the image. The proposed approach replaces the Discrete Cosine Transform phase of Conventional JPEG with a combination of clustering and Run Length Encoding so as to handle redundant data in the image effectively. Simulation with respect to benchmark data indicates improved compression (42.5%) in relation to existing solutions. Image quality metrices such as PSNR, structural similarity have also been tested and it is observed that the proposed approach achieves significant compression ratio with negligible loss in visual quality.

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A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications

Cited by 112 publications

References 98 publications

A Systematic Review on Harmony Search Algorithm: Theory, Literature, and Applications

A Systematic Review on Harmony Search Algorithm: Theory, Literature, and Applications

HASPO: Harmony Search-Based Parameter Optimization for Just-in-Time Software Defect Prediction in Maritime Software

An efficient and novel data clustering and run length encoding approach to image compression

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