Affiliation:
1. School of Business George Washington University Washington DC USA
2. Operations Research Department Naval Postgraduate School Monterey California USA
Abstract
AbstractIn multi‐agent search planning for a randomly moving and camouflaging target, we examine heterogeneous searchers that differ in terms of their endurance level, travel speed, and detection ability. This leads to a convex mixed‐integer nonlinear program, which we reformulate using three linearization techniques. We develop preprocessing steps, outer approximations via lazy constraints, and bundle‐based cutting plane methods to address large‐scale instances. Further specializations emerge when the target moves according to a Markov chain. We carry out an extensive numerical study to show the computational efficiency of our methods and to derive insights regarding which approach should be favored for which type of problem instance.
Funder
National Science Foundation of Sri Lanka
Office of Naval Research
Subject
Management Science and Operations Research,Ocean Engineering,Modeling and Simulation