Bi-objective dynamic weapon-target assignment problem with stability measure

Silav, Ahmet; Karasakal, Esra; Karasakal, Orhan

doi:10.1007/s10479-020-03919-8

Cited by 15 publications

(2 citation statements)

References 17 publications

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“…Hosein used the maximum marginal return algorithm and suboptimal algorithm, and it is efcient to obtain the bounds of the optimal solution. Silav et al [17] developed biobjective model for dynamic WTA, and a linearization approach is applied to the objective function. And the result showed that the approach can be used for real-time constrained WTA problem and can assist decision-making in a relatively short time.…”

Section: Literature Reviewmentioning

confidence: 99%

Weapon Target Assignment Model for Small Unit Ground Combat Using Mixed Integer Nonlinear Program and Lagrangian Relaxation

Kim¹,

Cho

Han

et al. 2022

Mathematical Problems in Engineering

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The importance of the weapon target assignment problem is increasing as weapon systems are expected to become intelligent and unmanned on the future battlefield. This study discusses the weapon-target assignment in small-scale ground force combat, which has not been addressed much in other studies. In ground combat, target assignment means the start of an engagement, so assignment should be made taking into account not only the probability of killing an enemy but also the probability of surviving friendly forces. We introduce the WTAG (WTA ground) model that reflects these characteristics and describes methodologies for solving the problem including mixed integer nonlinear problems and Lagrangian relaxation approaches. Our finding is that the algorithm presented can efficiently provide the bounds of the problem in a practical size.

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Section: Literature Reviewmentioning

confidence: 99%

Weapon Target Assignment Model for Small Unit Ground Combat Using Mixed Integer Nonlinear Program and Lagrangian Relaxation

Kim¹,

Cho

Han

et al. 2022

Mathematical Problems in Engineering

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show abstract

“…Ahner [10] considers the uncertainty of the second stage and assigned the available weapons by including the expected value of the sec-ond stage in the first stage target. Silav [11] considers that the incoming air targets are random, and defines the objective function as the maximization of the probability of no-leaker in the engagement sequence of the weapon system. Based on the above model, various algorithms have been proposed to solve the DWTA problem since the 1970s.…”

Section: Introductionmentioning

confidence: 99%

A Time-Driven Dynamic Weapon Target Assignment Method

Liu,

Li,

Wang

et al. 2023

IEEE Access

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The traditional dynamic weapon target assignment model is a combination of multiple static weapon target assignment stages. The assignment of the next stage is carried out after the result of the previous static weapon target assignment is settled. However, between two static weapon target assignment stages, the threat ranking of multiple targets may change with time, and the traditional dynamic weapon target assignment model does not take this time issue into consideration. This paper proposes a "time sampling dynamic weapon assignment model". This model divides the decision-making stage by setting the time interval of data collection, and it can capture the real-time changes in the target threat degree and make timely decisions. With this model, this study designed a dynamic weapon target assignment method based on the reinforcement learning algorithm. Additionally, according to this method, a comparative experiment with different sampling time divisions was designed, and a better sampling time division method was obtained. Finally, a comparative experiment between the reinforcement learning algorithm and the traditional heuristic algorithm was designed in this study. The simulation results show that, compared with the traditional heuristic algorithm, the proposed assignment model and the reinforcement learning algorithm are better in terms of decision-making timeliness and global considerations.INDEX TERMS dynamic weapon target assignment; simulation model; reinforcement learning; heuristic algorithm; PPO algorithm.

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Naval Air Defense Planning problem: A novel formulation and heuristics

Arslan,

Karasakal,

Kırca

2024

Naval Research Logistics

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This article focuses on air defense in maritime environment, which involves protecting friendly naval assets from aerial threats. Specifically, we define and address the Naval Air Defense Planning (NADP) problem, which consists of maneuvering decisions of the ships and scheduling weapons and sensors to the threats in order to maximize the total expected survival probability of friendly units. The NADP problem is more realistic and applicable than previous studies, as it considers features such as sensor assignment requirements, weapon and sensor blind sectors, sequence‐dependent setup times, and ship's infrared/radar signature. In this study, a mixed‐integer nonlinear programming model of the NADP problem is presented and heuristic solution approaches are developed. Computational results demonstrate that these heuristic approaches are both fast and efficient in solving the NADP problem.

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Bi-objective dynamic weapon-target assignment problem with stability measure

Cited by 15 publications

References 17 publications

Weapon Target Assignment Model for Small Unit Ground Combat Using Mixed Integer Nonlinear Program and Lagrangian Relaxation

Weapon Target Assignment Model for Small Unit Ground Combat Using Mixed Integer Nonlinear Program and Lagrangian Relaxation

A Time-Driven Dynamic Weapon Target Assignment Method

Naval Air Defense Planning problem: A novel formulation and heuristics

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