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A New Ant Colony Optimization Method Considering Intensification and Diversification

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PRIMA 2013: Principles and Practice of Multi-Agent Systems (PRIMA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8291))

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Abstract

Ant colony optimization (ACO) is a meta-heuristic algorithm inspired by foraging behavior of ants and is one of the most well known swarm intelligence algorithms for solving the Traveling Salesman Problem (TSP) because of its simpleness and quality. In this paper we will propose an ACO based algorithm called ASwide that adds simple but powerful factors in the pheromone updating formula. To check the efficiency of our algorithm we did several computer experiments and confirmed that ASwide generates an acceptable solution stably compared with other methods.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya-shi, 466-8555, Japan

    Mitsuru Haga & Shohei Kato

Authors
  1. Mitsuru Haga
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  2. Shohei Kato
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Editor information

Editors and Affiliations

  1. Dipartimento di Informatica,, Università degli Studi di Torino, via Pessinetto 12,, 10149, Torino, Italy

    Guido Boella

  2. Division of Mathematical Sciences, Nanyang Technological University, Singapore

    Edith Elkind

  3. Department of Information Science, University of Otago, Dunedin, New Zealand

    Bastin Tony Roy Savarimuthu  & Martin K. Purvis  & 

  4. Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands

    Frank Dignum

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Haga, M., Kato, S. (2013). A New Ant Colony Optimization Method Considering Intensification and Diversification. In: Boella, G., Elkind, E., Savarimuthu, B.T.R., Dignum, F., Purvis, M.K. (eds) PRIMA 2013: Principles and Practice of Multi-Agent Systems. PRIMA 2013. Lecture Notes in Computer Science(), vol 8291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44927-7_33

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  • DOI: https://doi.org/10.1007/978-3-642-44927-7_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-44926-0

  • Online ISBN: 978-3-642-44927-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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