@inproceedings{ff72201072534046bcb5981bf4971a3e,
title = "Sensor-weapon joint management based on improved genetic algorithm",
abstract = "In the modern combat operation, the fixed combination of sensors and weapons are divided into separate parts, allowing better sensors to match with better weapons. As a result, the shooting effectiveness of weapons can be improved. In order to maximum the benefit of the combat operation, the optimization problem to describe operational effectiveness of sensors and weapons is established. Furthermore the method to solve this problem is studied. The method is an improved genetic algorithm, whose parent populations are divided into three components, by adjusting the proportion of each component, the searching area can be dynamically changed (ds-GA). The simulation results show that ds-GA is a suitable method which could solve the sensor-weapon joint management problem in a short time.",
keywords = "Genetic Algorithm, Searching Area, Selection Process, Sensor-Weapon Joint Management",
author = "Jian Wang and Chen Chen",
note = "Publisher Copyright: {\textcopyright} 2015 Technical Committee on Control Theory, Chinese Association of Automation.; 34th Chinese Control Conference, CCC 2015 ; Conference date: 28-07-2015 Through 30-07-2015",
year = "2015",
month = sep,
day = "11",
doi = "10.1109/ChiCC.2015.7260057",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "2738--2742",
editor = "Qianchuan Zhao and Shirong Liu",
booktitle = "Proceedings of the 34th Chinese Control Conference, CCC 2015",
address = "United States",
}