2008
DOI: 10.1016/j.amc.2008.05.148
|View full text |Cite
|
Sign up to set email alerts
|

Optimization based on symbiotic multi-species coevolution

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
19
0

Year Published

2009
2009
2018
2018

Publication Types

Select...
9
1

Relationship

4
6

Authors

Journals

citations
Cited by 39 publications
(22 citation statements)
references
References 26 publications
0
19
0
Order By: Relevance
“…Our several previous studies suggest a static RFID network optimization model based on evolutionary algorithms and swarm intelligence [17,29,31]. Without considering the dynamic of RFID tags, it was shown that RFID network optimization can be modeled as a multi-objective optimization problem, where coverage, interference, economic efficiency and network load balance are particularly considered as the primary requirements of the RFID system.…”
Section: Dynamic Optimization For Rfid Networkmentioning
confidence: 99%
“…Our several previous studies suggest a static RFID network optimization model based on evolutionary algorithms and swarm intelligence [17,29,31]. Without considering the dynamic of RFID tags, it was shown that RFID network optimization can be modeled as a multi-objective optimization problem, where coverage, interference, economic efficiency and network load balance are particularly considered as the primary requirements of the RFID system.…”
Section: Dynamic Optimization For Rfid Networkmentioning
confidence: 99%
“…The classical test suite includes ten 30-dimension benchmark functions, which are commonly used in evolutionary computation literature [17,27,33] to show solution quality and convergence rate. The first problem is the unimodal Sphere function (f 1 ) that is easy to solve.…”
Section: Classical Test Functionsmentioning
confidence: 99%
“…cellular radio network, wireless sensor network, and RFID network), such as Evolution Strategies, Genetic Algorithm, and Particle swarm Optimization [5]. In this paper, a novel multi-swarm optimizer, called PS 2 O [6], which extend the single population PSO to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations, is proposed for solving the networking problem in RFID systems. By incorporating the new degree of complexity, PS 2 O can accommodate a considerable potential for solving more complex problems.…”
Section: Introductionmentioning
confidence: 99%