A grid-based MOEA guided by synchronous self-adaptive local diversity-preserving for constrained optimization of an extended-range small self-defense missile

Miniaturized airborne antimissile interception systems can increase a fighter’s payload capacity and enhance active protection capability. However, conventional small missiles have a large aspect ratio, which reduces propulsion system reliability and aerodynamic maneuverability. This study proposes a two-stage separable extended-range missile design to solve this problem. The multidisciplinary design optimization (MDO) model of the extended-range small self-defense missile (ERSSDM) with a nonlinear design objective space and multiple constraints produces an unwonted diversity loss problem, restricting the application of heuristic multi-objective algorithms to missile MDO problems. Therefore, two concepts-grid crowding degree and relaxation factor-are introduced, and a grid-based multi-objective evolutionary algorithm (MOEA), GMOEA-SSLD, is proposed and coupled to the MDO model of this weapon system to obtain Pareto optimal designs with well-preserved diversity. This algorithm, which uses grid-based techniques and synchronous diversity-preserving approaches, eliminates the necessity for coordinate specification and improves the design efficiency in the multidisciplinary optimization of the small missile as compared to another coordinate-based MOEA. The MDO model is decoupled to some extent based on an efficient global sensitivity analysis (GSA) approach.