Improved Quantum Immune Clonic Algorithm in Weapon-Target Assignment under Conditions of Network Confrontation Environment
FENG Chao
JING Xiaoning
LI Qiuni
XIA Fei
FEI Kai
Abstract：In consideration of the principles that attack benefits of network combined targets with targets are maximal and its own consumption is minimal in total,a multi-obj ective optimization model is estab-lished under conditions of network confrontation environment in fire distribution.Under conditions of ran-dom network topology introduced,the effect of fire distribution corresponding to the random network is analyzed.This paper adopts quantum-inspired immune clonic multi-obj ective optimization algorithm to solve the model of fire distribution.Though experimental simulation,the change circumstances of the total attack benefits are analyzed by using different cost ammunition.The attack efficiency of the fire distribu-tion scheme increases by 23% by using the improved algorithm over the fire distribution scheme by using standard algorithm.The convergence of the algorithm and superiority of Pareto solution distribution are studied.The experiments demonstrate that the Pareto efficiency solution distribution increases 42% by u-sing the improved algorithm over using the standard algorithm.The superiority of the model and the effi-ciency of the algorithm are verified.
Keywords：weapon-target assignmentQICMOAcomplex networksnetwork-centric warfarePareto effi-ciency
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 29-34 )