Myopic and Presbyopic Approaches to a Multi-Sensor, Multi-Target Resource Allocation Problem

Harilaos N. Psaraftis, Anastassios N. Perakis

Research output: Contribution to conferencePaperResearchpeer-review

Abstract

This paper takes advantage of recent results on the probabilistic modeling of the
ocean acoustic detection process to develop two approximate procedures for tackling a simplified version of the m-sensor, n-target resource allocation problem. The first procedure is termed "myopic" (short-sighted) and applies if we are interested to maximize the expected number of targets held in the short-run. This second procedure is termed "presbyopic" (far-sighted) and applies if we are interested to obtain the maximum expected number of targets held in the long-run, that is, when the system is in the steady state. Both approaches are suboptimal because they neglect, each in a different way, the interdependence
of allocation decisions through time.
We formulate the myopic case as a Linear Programming "Assignment" optimization problem whose inputs are dynamically updated through time. Then we do the same for the presbyopic case. It is seen that if a presbyopic policy is followed, no switching decisions will ever occur. We then extend the myopic formulation to incorporate a general target-holding reward function as well as switching costs. We present some illustrative examples, applying both approaches to simulated data. We also present a comparison of both methods with an exact Stochastic Dynamic Programming approach we had developed earlier for problems of very small size.
Original languageEnglish
Publication date1982
Number of pages8
Publication statusPublished - 1982
Externally publishedYes
Event5th MIT/ONR Symposium on Command and Control - Monterey, United States
Duration: 23 Aug 198227 Aug 1982

Conference

Conference5th MIT/ONR Symposium on Command and Control
CountryUnited States
CityMonterey
Period23/08/198227/08/1982

Cite this

Psaraftis, H. N., & Perakis, A. N. (1982). Myopic and Presbyopic Approaches to a Multi-Sensor, Multi-Target Resource Allocation Problem. Paper presented at 5th MIT/ONR Symposium on Command and Control , Monterey, United States.