Nonlinear optimal model and solving algorithms for platform planning problem in battlefield

Abstract

Platform planning is one of the important problems in the command and control (C2) field. Hereto, we analyze the platform planning problem and present nonlinear optimal model aiming at maximizing the task completion qualities. Firstly, we take into account the relation among tasks and build the single task nonlinear optimal model with a set of platform constraints. The Lagrange relaxation method and the pruning strategy are used to solve the model. Secondly, this paper presents optimization-based planning algorithms for efficiently allocating platforms to multiple tasks. To achieve the balance of the resource assignments among tasks, the m-best assignment algorithm and the pair-wise exchange (PWE) method are used to maximize multiple tasks completion qualities. Finally, a series of experiments are designed to verify the superiority and effectiveness of the proposed model and algorithms.