Skip to main content

Knowledge-Based Techniques for Constraints Satisfaction in Resource Allocation Problems

  • Conference paper
  • First Online:
AI 2002: Advances in Artificial Intelligence (AI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2557))

Included in the following conference series:

  • 1128 Accesses

Abstract

Knowledge-based techniques are as effective as mathematical techniques for satisfying constraints in manpower resource allocation (MRA) problems. Our knowledge-based techniques allow direct implementation for logical reasoning, reduce efforts in setting up and interpreting rules of constraints, fair well in giving correct solutions, and are adaptable to human rules. This class of problems arises in the management of manpower for organisations that provide round-the-clock services, requiring special expertise and experience to ensure that resultant rosters optimally match the skills of the available manpower resources to the various conditions and requisites of the deployment posts.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mohamed, K.A., Datta, A., Kozera, R. (2002). Knowledge-Based Techniques for Constraints Satisfaction in Resource Allocation Problems. In: McKay, B., Slaney, J. (eds) AI 2002: Advances in Artificial Intelligence. AI 2002. Lecture Notes in Computer Science(), vol 2557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36187-1_73

Download citation

  • DOI: https://doi.org/10.1007/3-540-36187-1_73

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00197-3

  • Online ISBN: 978-3-540-36187-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics