Abstract
The weapon target assignment (WTA) problem is the crucial decision support in Command & Control (C2). In the classic WTA model, the point-to-point saturation salvo has a low efficiency-cost ratio when the swarming targets, which have the advantage of low casualty, low cost and recyclable, become the major operational units. The constraint is less studied for the operational intention of the decision-maker. In this paper, a constrained multi-objective weapon target assignment (CMWTA) model is formulated for area targets. The optimization objectives are minimizing collateral damage and resource consumption. The multi-constraint is derived from the actual operational requirements of security evasion, damage threshold, and preference assignment. To solve CMWTA efficiently, a novel multi-objective optimization evolutionary algorithm (MOEA) is proposed to obtain the non-dominated solutions as the alternative plans for the decision-maker. A self-adaptive sorting algorithm is proposed to guarantee the completeness of the Pareto-optimal set, and a cooperative evolutionary mechanism is adopted to strengthen the convergence. For handling multi-constraint, a repair mechanism is proposed to improve the quality of infeasible solutions, and the measurement of constraint violation is designed to evaluate the infeasible solutions. A variant of the convergence metric is introduced to evaluate the algorithms solving multi-objective weapon target assignment (MWTA) problem. The experimental results show the effectiveness and superiority of the proposed approaches.
Highlights
The weapon target assignment (WTA), which is known as Weapon Allocation or Weapon Assignment (WA), refers to the reactive assignment of defensive weapons to counter identified threats
This paper focuses on the static WTA (SWTA) problem, and the review of the Dusmanta Kumar Mohanta .WTA (DWTA) problem can refer to [3], [4]
The display of the optimal non-dominated solutions obtained by multi-objective optimization evolutionary algorithm (MOEA)-constrained multi-objective weapon target assignment (CMWTA), non-dominated sorting genetic algorithm (NSGA)-II-SP, SPEA2-CDP, SPEA2-SP, and MOEA based on decomposition (MOEA/D)-WTA-SP solving scenario 2 over 30 independent runs
Summary
The weapon target assignment (WTA), which is known as Weapon Allocation or Weapon Assignment (WA), refers to the reactive assignment of defensive weapons to counter identified threats. The objectives and constraints are various, the point-to-point SWTA model is essentially a combinatorial optimization problem. Because of the insensitivity of model scale and constraints, the evolutionary algorithm performs excellently on solving the WTA problem. As TSP and VPR, the SWTA model of this attack mode is a combinatorial optimization problem (COP) and has been studied by the corresponding algorithms. (2) As the decision support of C2, the constraints of the major models reflect the less intention of the decisionmaker For these requirements, an alternative strategy is employing weapons with lethal radius to attack the targets, which are viewed as area targets in Threat Evaluation (TE), by collateral damage. A variant of convergence metric is introduced to evaluate the performance of algorithms on solving MWTA which takes the operational effect and resource consumption as optimization objectives.
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