Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Formation of adjective, noun and verb concepts through affordances
Download
index.pdf
Date
2012
Author
Turan, Ayşe
Metadata
Show full item record
Item Usage Stats
2
views
0
downloads
Within the air defense domain, the Weapon-Target Allocation problem is a fundamental problem. This problem deals with the allocation of a set ofiring units or weapons to a set of hostile targets so that the total expected effect on targets is maximized. The Weapon-Target Allocation problem has been proven to be NP-Complete by Lloyd and Witsenhausen [14]. In this thesis, the use of various algorithms including search algorithms, maximum marginal return algorithms, evolutionary algorithms and bipartite graph matching algorithms are demonstrated to solve the problem. Algorithms from the literature are adjusted to the problem and implemented. In addition, existing algorithms are improved by taking care of the maximum allowed time criterion. A testbed is developed to be able to compare the algorithms. The developed testbed allows users to implement new algorithms and compare the algorithms that are selected by the users easily. Using the testbed, implemented algorithms are compared based on optimality and performance criteria. The results are examined and by combining the algorithms that give better results, a new algorithm is proposed to solve the problem more effciently. The proposed algorithm is also compared to the other algorithms and computational results of the algorithms are presented
Subject Keywords
Computer algorithms.
,
Projectile points.
,
Targets (Shooting).
,
Weapons,
,
Graph algorithms.
URI
http://etd.lib.metu.edu.tr/upload/12614452/index.pdf
https://hdl.handle.net/11511/21666
Collections
Graduate School of Natural and Applied Sciences, Thesis