Minimum Span Frequency Assignment Based on a Multiagent Evolutionary Algorithm

Jing Liu, Jinshu Li, Weicai Zhong, Li Zhang and Ruochen Liu
Additional contact information
Jing Liu: Xidian University, China
Jinshu Li: Xidian University, China
Weicai Zhong: Northwest A&F University, China
Li Zhang: Soochow University, China
Ruochen Liu: Xidian University, China

International Journal of Swarm Intelligence Research (IJSIR), 2011, vol. 2, issue 3, 29-42

Abstract: In frequency assignment problems (FAPs), separation of the frequencies assigned to the transmitters is necessary to avoid the interference. However, unnecessary separation causes an excess requirement of spectrum, the cost of which may be very high. Since FAPs are closely related to T-coloring problems (TCP), multiagent systems and evolutionary algorithms are combined to form a new algorithm for minimum span FAPs on the basis of the model of TCP, which is named as Multiagent Evolutionary Algorithm for Minimum Span FAPs (MAEA-MSFAPs). The objective of MAEA-MSFAPs is to minimize the frequency spectrum required for a given level of reception quality over the network. In MAEA-MSFAPs, all agents live in a latticelike environment. Making use of the designed behaviors, MAEA-MSFAPs realizes the ability of agents to sense and act on the environment in which they live. During the process of interacting with the environment and other agents, each agent increases the energy as much as possible so that MAEA-MSFAPs can find the optima. Experimental results on TCP with different sizes and Philadelphia benchmark for FAPs show that MAEA-MSFAPs have a good performance and outperform the compared methods.

Date: 2011
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jsir.2011070103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:2:y:2011:i:3:p:29-42

Access Statistics for this article

International Journal of Swarm Intelligence Research (IJSIR) is currently edited by Yuhui Shi

More articles in International Journal of Swarm Intelligence Research (IJSIR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().