A comparative analysis of information acquisition mechanisms for discrete resource allocation

Benjamin Shao, H. Raghav Rao

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Discrete resource allocation problems (RAPs) are concerned with making decisions that result in an optimal deployment of indivisible scarce resources among a group of agents so as to achieve the maximum aggregate utility. One prerequisite for solving the discrete RAP is that the decision maker be cognizant of the individual utility functions for the agents involved. When an agent's preference information is not available, the decision maker needs to gather such information through an inquiry process. The information acquisition process entails its own costs such as communication costs and computation costs. In this paper, three different information inference mechanisms-merging, ranking, and entropy-are proposed and compared for the information acquisition process in the discrete RAP. It is found that the merging mechanism results in the least computation costs for the decision maker while the entropy mechanism incurs the least communication costs.

Original languageEnglish (US)
Pages (from-to)199-209
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
Issue number3
StatePublished - May 2001


  • Decision analysis
  • Discrete resource allocation
  • Entropy
  • Information acquisition
  • Information economics
  • Merging
  • Ranking
  • Utility function

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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