Cooperative particle swarm optimization with reference-point-based prediction strategy for dynamic multiobjective optimization

Dynamic multiaircraft cooperative suppression interference array (MACSIA) optimization problem is a typical dynamic multiobjective optimization problem. In this paper, the sum of the distance between each jamming aircraft and the enemy air defense radar network center and the minimum width of the safety area for route planning are taken as the objective functions. The dynamic changes in the battlefield environment are reduced to two cases. One is that the location of the enemy air defense radar is mobile, but the number remains the same. The other is that the number of the enemy air defense radars is variable, but the original location remains unchanged. Thus, two dynamic multiobjective optimization models of dynamic MACSIA are constructed. The dynamic multiobjective particle swarm optimization algorithm is used to solve the two models, respectively. The optimal dynamic MACSIA schemes which satisfy the limitation of the given suppression interference effect and ensure the safety of the jamming aircraft themselves are obtained by simulation experiments. And then verify the correctness of the constructed dynamic multiobjective optimization model, as well as the feasibility and effectiveness of the dynamic multiobjective particle swarm optimization algorithm in solving dynamic MACSIA problem.

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Particle Swarm Optimization and strength pareto to solve multiobjective optimization problems

International Journal of Applied Electromagnetics and Mechanics ◽

10.3233/jae-131717 ◽

2013 ◽

Vol 43 (1-2) ◽

pp. 137-149 ◽

Cited By ~ 3

Author(s):

Leandro Zavarez Barbosa ◽

Leandro dos S. Coelho ◽

Luiz Lebensztajn

Keyword(s):

Particle Swarm Optimization ◽

Multiobjective Optimization ◽

Optimization Problems ◽

Particle Swarm ◽

Swarm Optimization ◽

Multiobjective Optimization Problems

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Research on Multiaircraft Cooperative Suppression Interference Array Based on an Improved Multiobjective Particle Swarm Optimization Algorithm

Mathematical Problems in Engineering ◽

10.1155/2017/9843735 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Huan Zhang ◽

Rennong Yang ◽

Changyue Sun ◽

Haiyan Han

Keyword(s):

Particle Swarm Optimization ◽

Multiobjective Optimization ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Particle Swarm ◽

Swarm Optimization ◽

Minimum Width ◽

Air Defense ◽

Radar Network ◽

Multiobjective Particle Swarm Optimization

For the problem of multiaircraft cooperative suppression interference array (MACSIA) against the enemy air defense radar network in electronic warfare mission planning, firstly, the concept of route planning security zone is proposed and the solution to get the minimum width of security zone based on mathematical morphology is put forward. Secondly, the minimum width of security zone and the sum of the distance between each jamming aircraft and the center of radar network are regarded as objective function, and the multiobjective optimization model of MACSIA is built, and then an improved multiobjective particle swarm optimization algorithm is used to solve the model. The decomposition mechanism is adopted and the proportional distribution is used to maintain diversity of the new found nondominated solutions. Finally, the Pareto optimal solutions are analyzed by simulation, and the optimal MACSIA schemes of each jamming aircraft suppression against the enemy air defense radar network are obtained and verify that the built multiobjective optimization model is corrected. It also shows that the improved multiobjective particle swarm optimization algorithm for solving the problem of MACSIA is feasible and effective.

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