Selected Papers from the 3rd International Conference on the Harmony Search Algorithm (ICHSA 2017)

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (15 May 2017) | Viewed by 5935

Special Issue Editor


E-Mail Website1 Website2
Guest Editor
1. OPTIMA Area, TECNALIA, Basque Research & Technology Alliance (BRTA), 48160 Zamudio, Bizkaia, Spain
2. Communications Engineering, University of the Basque Country (UPV/EHU), 48013 Bilbao, Bizkaia, Spain
Interests: machine learning; deep learning; meta-heuristic optimization; explainable artificial intelligence; responsible artificial intelligence; stream learning
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Special Issue Information

Dear Colleagues,

It is my pleasure to introduce you to this Special Issue of Algorithms, which includes extended versions of the best papers presented at the 3rd International Conference on the Harmony Search Algorithm (ICHSA 2017,  Bilbao, Spain, 22–24 February 2017). Papers submitted to this Special Issue will represent the core and state of the art around this meta-heuristic solver, which has gained momentum during the last decade attracting more than 15,000 citations so far. The Special Issue will consider theoretical insights on the algorithm itself and present practical applications in different fields. Other contributions related to swarm intelligence, evolutionary computation and in general, bio-inspired optimization and processing will be considered.

A list of potential papers will be decided by the steering committee of the conference during its celebration. Invitations will be subsequently sent out to the authors of the selected papers, which will be invited to extend their work (at least 50%, according to the editorial policy) and submit it to Algorithms. Nevertheless, the Special Issue is absolutely open to prospective authors that have not attended the conference, provided that their contributed manuscripts are aligned with the overall thematic of the conference.

Dr. Javier Del Ser Lorente
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Harmony Search
  • bio-inspired optimization
  • swarm intelligence
  • evolutionary computation

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Published Papers (1 paper)

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1618 KiB  
Article
Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification
by Yu Feng, Jianzhong Zhou and Muhammad Tayyab
Algorithms 2017, 10(1), 14; https://doi.org/10.3390/a10010014 - 14 Jan 2017
Cited by 7 | Viewed by 5048
Abstract
This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, [...] Read more.
This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems. Full article
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