A DC programming approach for planning a multisensor multizone search for a target

In this paper, we consider a well-known problem in the general area of search theory: planning a multisensor in multizone search so as to maximize the probability of detection of a target under a given resource effort to be shared. We propose a new optimization model that is a nonlinear mixed 0-1 programming problem. This problem is then reformulated as a DC (Difference of Convex) functions program via an exact penalty technique. DC programming and DCA (DC algorithm) have been investigated for solving the resulting DC program. Numerical experiments demonstrate the efficiency and the superiority of the proposed algorithm in comparison with the existing method.