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A multi-objective optimization framework with rule-based initialization for multi-stage missile target allocation.

Shiqi Zou1, Xiaoping Shi1, Shenmin Song2

  • 1Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China.

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|May 10, 2023
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Summary
This summary is machine-generated.

This study introduces a new optimization framework for multi-stage missile target allocation (M-MTA), balancing target survivability and missile cost. The proposed algorithm, NSGA-MTA, demonstrates superior performance in diversity and convergence compared to existing methods.

Keywords:
multi-objective optimizationnon-dominated sortingrandom repair strategyrule-based initializationweapon-target assignment

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Area of Science:

  • Operations Research
  • Computer Science
  • Defense Systems Engineering

Background:

  • The multi-stage missile target allocation (M-MTA) problem is critical in defense and complex systems.
  • Existing methods often struggle to balance competing objectives like target survivability and resource consumption.

Purpose of the Study:

  • To develop a novel multi-objective optimization framework for the M-MTA problem.
  • To address the trade-off between minimizing target survivability and missile cost consumption.
  • To propose an effective algorithm for solving the constrained M-MTA problem.

Main Methods:

  • A constrained M-MTA model was formulated.
  • A novel multi-objective optimization algorithm (NSGA-MTA) was proposed, utilizing hybrid encoding.
  • Rule-based initialization, non-dominated sorting, and genetic operators with greedy mechanisms and repair strategies were employed.

Main Results:

  • NSGA-MTA exhibited enhanced diversity and convergence compared to current algorithms across 15 scenarios.
  • The proposed strategies were validated using the Taguchi method, confirming their practical benefits.
  • The algorithm effectively handled constraints while maintaining solution diversity.

Conclusions:

  • The developed NSGA-MTA framework provides a superior approach to M-MTA.
  • The integrated strategies significantly improve optimization performance for complex allocation problems.
  • This research offers practical advancements for missile defense and similar optimization challenges.