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GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
14 years 3 months ago
Two-level of nondominated solutions approach to multiobjective particle swarm optimization
In multiobjective particle swarm optimization (MOPSO) methods, selecting the local best and the global best for each particle of the population has a great impact on the convergen...
M. A. Abido
KIVS
2011
Springer
12 years 11 months ago
A Feasibility Check for Geographical Cluster Based Routing under Inaccurate Node Localization in Wireless Sensor Networks
Localized geographic single path routing along a wireless network graph requires exact location information about the network nodes to assure message delivery guarantees. Node loc...
Hannes Frey, Ranjith Pillay
IDA
2003
Springer
14 years 2 months ago
An Iterated Local Search Approach for Minimum Sum-of-Squares Clustering
Abstract. Since minimum sum-of-squares clustering (MSSC) is an NPhard combinatorial optimization problem, applying techniques from global optimization appears to be promising for r...
Peter Merz
IJCNN
2006
IEEE
14 years 2 months ago
Global Reinforcement Learning in Neural Networks with Stochastic Synapses
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
Xiaolong Ma, Konstantin Likharev
MOBIHOC
2008
ACM
14 years 8 months ago
Construction algorithms for k-connected m-dominating sets in wireless sensor networks
A Connected Dominating Set (CDS) working as a virtual backbone is an effective way to decrease the overhead of routing in a wireless sensor network. Furthermore, a kConnected m-Do...
Yiwei Wu, Yingshu Li