Multi-agent decision support system for missile defense based on improved PSO algorithm
Authored by Zilong Cheng, Li Fan, Yulin Zhang
Date Published: 2017
DOI: 10.21629/jsee.2017.03.11
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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.
Tags
Agent-based modeling
Optimization
Framework
Missile defense system
Decision support system
(dss)
Variable neighborhood
Negative selection
Particle swarm
optimization (pso)