Achieving Realistic Levels of Defensive Hedging Based on Non-monotonic and Multi-attribute Terrorist Utility Functions

Vicki Marion Bier (), Jaime Marie Bonorato and Chen Wang
Additional contact information
Vicki Marion Bier: University of Wisconsin-Madison
Jaime Marie Bonorato: University of Wisconsin-Madison
Chen Wang: University of Wisconsin-Madison

Chapter Chapter 6 in Handbook of Operations Research for Homeland Security, 2013, pp 125-139 from Springer

Abstract: Abstract This chapter addresses the problem of allocating limited resources to defend a set of targets. When there is uncertainty about which targets the terrorists are most likely to attack, decision makers are likely to insist on some degree of “hedging” (defending targets with only moderate value). The work discussed in this chapter uses game theory to find the optimal strategy for the defender and shows that non-monotonic attacker objective functions do typically yield greater hedging.

Keywords: Attribute Weight; Optimal Resource Allocation; Fiscal Year; Foreign Land; Attack Preference (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4614-5278-2_6

Ordering information: This item can be ordered from
http://www.springer.com/9781461452782

DOI: 10.1007/978-1-4614-5278-2_6

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().