WEAPON-TARGET ASSIGNMENT FOR AIR DEFENSE OF NAVAL FORCES: MODELS AND HEURISTICS

Date

2024-9-5

Author

Arslan, Caner

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Air defense in maritime environment is the protection of friendly naval assets against aerial threats. The objective of minimizing the threat to the defended assets requires optimal allocation of scarce defense resources to the targets. Flexible command and control functionality is necessary to handle the dynamic nature of events in air defense. Coordination and automation should be ensured between sensors and weapons in single ship or task group air defense environment. To provide effective decision support on the automation of the decisions, fast and efficient algorithms are needed in the command-and-control systems of ships. The naval air defense planning (NADP) problem consists of maneuvering decisions of the ships and assigning/scheduling weapons and sensors to threats so that the total expected survival probability of friendly units is maximized. The NADP problem can be defined as a specific version of the Weapon Target Assignment (WTA) problem, which has been extensively studied in the literature since 1950s. Compared to other studies, the NADP problem includes new features that makes the problem definition more realistic and applicable. It also deals with sensor assignment requirements, weapon/sensor blind sectors, sequence dependent setup times and ship’s radar signature. In this thesis work, the development of exact/heuristic solution approaches that provide fast and efficient decision support on the automation of the NADP decisions is aimed. A mixed-integer nonlinear programming (MINLP) model of the NADP problem is presented and heuristic solution approaches are developed for both Static and Dynamic problem. The computational results demonstrate that these heuristic approaches are both fast and efficient in solving the NADP problem.

Subject Keywords

Deniz Hava Savunma, Silah-Hedef Atama, Angajman Çizelgeleme, Savaş Yönetim, Karar Destek Otomasyonu, Askeri Yöneylem Araştırması

URI

https://hdl.handle.net/11511/111327

Collections

Graduate School of Natural and Applied Sciences, Thesis