Special Issue "Bio-inspired Algorithms for Combinatorial Problems"


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

Deadline for manuscript submissions: closed (31 March 2014)

Special Issue Editors

Guest Editor
Prof. Dr. Ruay-Shiung Chang
Department of Computer Science and Information Engineering, National Dong Hwa University, No. 1, Section 2, Dashieh Road, Shoufeng, Hualien, Taiwan
Website: http://www.csie.ndhu.edu.tw/~rschang
E-Mail: rschang@mail.ndhu.edu.tw
Phone: +886 3 8634016
Fax: +886 3 8634010
Interests: wireless networks; sensor networks; internet; cloud computing

Guest Editor
Prof. Dr. Sheng-Lung Peng
Department of Computer Science and Information Engineering, National Dong Hwa University, No. 1, Section 2, Dashieh Road, Shoufeng, Hualien, Taiwan
Website: http://gba.csie.ndhu.edu.tw/english/english.html
E-Mail: slpeng@mail.ndhu.edu.tw
Phone: +886 3 8634026
Fax: +886 3 8634010
Interests: graph algorithms; bioinformatics

Special Issue Information

Dear Colleagues,

There is evidence that nature is a great source for inspirations to both develop intelligent systems and provide solutions to complicated problems. Taking animals for an example, evolutionary pressure forces them to develop highly optimized organs and skills for their survival. Some of the organs and their behaviors can be learned to design algorithms for real-world problems. For example, it is interesting to know how a group of ants can locate a relatively short path between their food in a distant place and their nets. Of course we now know that a substance called pheromone that ants emit play an important role. But can computer simulate ants' behavior and use this path finding technique to solve problems in other disciplines? Ant Colony Optimization (ACO) algorithm (abbreviated Ant Algorithm) is the research that pursues problem solution in this direction. Similar cases are Bees Algorithms (BA), Genetic Algorithms (GA), Firefly Algorithms (FA) and so on.
In this special issue of "Bio-inspired Algorithms for Combinatorial Problems", we seek original research or practical application results in the area of bio-inspired algorithms for combinatorial problems.

Acceptable topics include, but are not limited to, the following:

  • Design and analysis of ACO algorithms
  • Design and analysis of Bees algorithms
  • Design and analysis of Firefly algorithms
  • Design and analysis of Genetic algorithms
  • Other swarm intelligence algorithms
  • Practical real-life applications of Bio-inspired algorithms
  • Limitations of Bio-inspired algorithms
  • Applications to NP-complete problems

Prof. Dr. Ruay-Shiung Chang
Prof. Dr. Sheng-Lung Peng
Guest Editors


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. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as 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 refereed through a 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 quarterly 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 300 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.


  • ant algorithm
  • combinatorial optimization algorithm
  • swarm intelligence
  • ant colony
  • ant heuristics

Published Papers (1 paper)

Algorithms 2013, 6(3), 442-456; doi:10.3390/a6030442
Received: 17 June 2013; in revised form: 15 July 2013 / Accepted: 31 July 2013 / Published: 6 August 2013
Show/Hide Abstract | Download PDF Full-text (239 KB)

Last update: 9 December 2013

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