A new optimal weapon target assignment method using an artificial fish swarm algorithm with survival evolution

Abstract

Purpose

Firepower conflicts usually decay the firepower plan's enforceability, thus incurring high survival risks. Previous studies have shown little attention to avoiding firepower conflicts during the weapon target assignment process. This research proposes a new constrained optimization model named Firepower Conflict Free WTA (FCFWTA) and designs a Survival Evolution (SE) strategy for Artificial Fish Swarm Algorithm (AFSA) to solve the complex constrained WTA problem. In this way, commanders can get more reliable firepower assignment decision support.

Design/methodology/approach

A new constrained optimization model named Firepower Conflict Free WTA (FCFWTA) is constructed. FCFWTA unifies firepower decision variables for different kinds of weapons and takes the firing time point as a clue for firepower conflict checking. The objective function of FCFWTA is the weighted sum of the minimum threat value rest rate (RRTV), maximum hit efficiency (HE) and minimum latest interception time percentage (PLT). Since previous algorithms do not check and resolve intermediate results during optimization, an adapted strategy named Survival Evolution is designed. It enables making full use of the limited firepower without adjusting the coordination scenario in execution.

Findings

The proposed method offers significant advantages in two aspects. Firstly, it effectively enhances the optimization results of WTA in the absence of firepower conflicts. Evidence from Figure. 6 confirms that without the proposed method, there is a high likelihood of generating invalid outcomes. After implementing firepower conflict check and resolution, there is a substantial degradation in the objective function value. Secondly, the method excels at equitably distributing firepower among multiple targets while also enhancing the overall interception probability, irrespective of the varying complexities presented by different scenarios. This ability to maintain balance and efficiency is crucial for tackling defense-related issues.

Research limitations/implications

Specifically, SE is tailored for MWMT problem under time and space constraints. This approach diverges significantly from conventional MWMT research, which typically focuses solely on ammunition quantity or firing range. Consequently, the primary objective was to verify the efficacy of this method. Test results indicated that SE does not exhibit uniform performance across different algorithms; while it significantly enhances the efficacy with PSO and AFSA, its influence is considerably diminished when applied to GA. It might be attributed to the inherent randomness associated with crossover and mutation, which can increase the likelihood of firepower conflicts, coupled with SE's reorganization of the chromosome.

Originality/value

The work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part.