Abstract:

Ballistic missile defense system (BMDS) is important
for its special role in ensuring national security and maintaining
strategic balance. Research on modeling and simulation of the
BMDS beforehand is essential as developing a real one requires
lots of manpower and resources. BMDS is a typical complex system
for its nonlinear, adaptive and uncertainty characteristics.
The agent-based modeling method is well suited for the complex
system whose overall behaviors are determined by interactions
among individual elements. A multi-agent decision support system
(DSS), which includes missile agent, radar agent and command
center agent, is established based on the studies of structure and
function of BMDS. Considering the constraints brought by radar,
intercept missile, offensive missile and commander, the objective
function of DSS is established. In order to dynamically generate
the optimal interception plan, the variable neighborhood negative
selection particle swarm optimization (VNNSPSO) algorithm is
proposed to support the decision making of DSS. The proposed
algorithm is compared with the standard PSO, constriction factor
PSO (CFPSO), inertia weight linear decrease PSO (LDPSO),
variable neighborhood PSO (VNPSO) algorithm from the aspects
of convergence rate, iteration number, average fitness value and
standard deviation. The simulation results verify the efficiency of
the proposed algorithm. The multi-agent DSS is developed through
the Repast simulation platform and the constructed DSS can generate
intercept plans automatically and support three-dimensional
dynamic display of missile defense process.