Weapon target assignment optimization for land based multi-air defense systems: A goal programming approach. (February 2019)

• Record Type: Journal Article
• Authors: Hocaoğlu, Mehmet Fatih
• Is Part Of: Computers & industrial engineering. Volume 128(2019)
• Page Start: 681
• Page End: 689
• Publication Date: 2019-02
• Subjects: Agent based simulation -- Air defense systems -- Goal programming -- Multi-objective optimization -- Non-linear optimization -- Resource allocation -- Weapon-target assignment; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2019.01.015
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: The optimization model generates weapon target assignments and a missile fire schedule. The model uses fire doctrine, C2 structures, defense strategies, and missile types. The model finds how many missiles are necessary for 100% success and a fire order. Goal programming approach gives optimum success level by minimum disturbance. The model is embedded in an air defense simulation scenario as an agent model. Abstract: This study addressed the issue of allocating the air defense missiles to incoming air targets to maximize the air defense effectiveness of land-based air defense systems. A constraint based nonlinear goal programming (multi-objective) model for weapon assignment problem to minimize survival probability was developed. The model not only gave optimum assignment but also resulted in engagement times and defense success for multi-defense sites. The model utilized parameters belonging to defense systems such as engagement duration, setup duration between engagements, command and control structures, fire doctrines, and defense strategies and parameters belonging to target such as probability of kill values, position, orientation, weapon load, target type, and course of actions inferred by current detection information. The simulation model has two-way usages. In the first usage, it obtains solution for the parameters given above under limited number of missiles. In the second usage, the model shows the amount of missile to be used to achieve the possible highest success with the parameters given above. To be able to use the optimization model in a simulation environment, a simulation model as an optimizer agent is developed and located in air defense simulation scenarios. The model collects input data, optimize assignments, calculates fire times, and schedules fire orders. This solution is exemplified by a land-based air defense example.