Skip to main content
SpringerLink
Log in

A Genetic Algorithm Approach to the Artillery Target Assignment Problem

  • Conference paper
  • First Online:
Book cover Computer and Information Sciences

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 62))

  • 834 Accesses

Abstract

In this work a new assignment problem with the name “Artillery Target Assignment Problem (ATAP)” is defined. ATAP is about assigning artillery guns to targets at different time instances while some objective functions are to be optimized. Since an assignment made for any time instance effect the value of the shooting ATAP is harder than the classical assignment problem. For two variations of ATAP genetic algorithm solutions with customized representations and genetic operators are developed and presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. C.A. Coello. Theoretical and Numerical Constraint-Handling Techniques Used with Evolutionary Algorithms: a Survey of the State of the Art. Computer Methods in Applied Mechanics and Engineering, 191(11–12):1245–1287, 2002.

    Article  MATH  MathSciNet  Google Scholar 

  2. GAlib: Matthew’s Genetic Algorithms Library. http://lancet.mit.edu/ga/

  3. C. Huaiping, L. Jingxu, C. Yingwu, W. Hao. Survey of the research on dynamic weapon-target assignment problem. J of Sys. Eng. & Elec., 17(3):559–565, 2006

    Article  Google Scholar 

  4. Z. Lee, S. Su, C. Lee. Efficiently Solving GeneralWeapon-Target Assignment Problem by Genetic Algorithms With Greedy Eugenics. IEEE T. on Sys. Man and Cyb., Part B, 33(1):113–121, 2003.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Middle East Technical University, Ankara, Turkey

    Burçin Sapaz, İsmail Hakki Toroslu & Göktürk Üçoluk

Authors
  1. Burçin Sapaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. İsmail Hakki Toroslu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Göktürk Üçoluk
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. , EEE Dept., Imperial College, Exhibition Road, London, SW72BT, United Kingdom

    Erol Gelenbe

  2. , EEE Dept., Imperial College, Exhibition Rd., London, SW72AZ, United Kingdom

    Ricardo Lent

  3. , EEE Dept., Imperial College, Exhibition Rd., London, SW72AZ, United Kingdom

    Georgia Sakellari

  4. , School of Biomedical Eng., Sci. and Heal, Drexel University, Bossone 702, 3120 Market Street, Philadelphia, 19104, Pennsylvania, USA

    Ahmet Sacan

  5. , Dept. of Computer Engineering, Middle East Technical University, Ankara, 06531, Turkey

    Hakki Toroslu

  6. Fac. Engineering, Dept. Computer Engineering, Middle East Technical University - METU, Ankara, 06531, Turkey

    Adnan Yazici

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media B.V.

About this paper

Cite this paper

Sapaz, B., Toroslu, İ.H., Üçoluk, G. (2011). A Genetic Algorithm Approach to the Artillery Target Assignment Problem. In: Gelenbe, E., Lent, R., Sakellari, G., Sacan, A., Toroslu, H., Yazici, A. (eds) Computer and Information Sciences. Lecture Notes in Electrical Engineering, vol 62. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9794-1_8

Download citation

  • DOI: https://doi.org/10.1007/978-90-481-9794-1_8

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-9793-4

  • Online ISBN: 978-90-481-9794-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation