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SAC
2004
ACM
13 years 11 months ago
A comparison of randomized and evolutionary approaches for optimizing base station site selection
It is increasingly important to optimally select base stations in the design of cellular networks, as customers demand cheaper and better wireless services. From a set of potentia...
Larry Raisanen, Roger M. Whitaker, Steve Hurley
TCS
2008
13 years 5 months ago
Comparing evolutionary algorithms to the (1+1)-EA
In this paper, we study the conditions in which the (1+1)-EA compares favorably to other evolutionary algorithms (EAs) in terms of fitness function distribution at given iteration...
Pavel A. Borisovsky, Anton V. Eremeev
AUSAI
2009
Springer
14 years 11 days ago
A Distance Metric for Evolutionary Many-Objective Optimization Algorithms Using User-Preferences
In this paper we propose to use a distance metric based on user-preferences to efficiently find solutions for many-objective problems. In a user-preference based algorithm a decis...
Upali K. Wickramasinghe, Xiaodong Li
CEC
2008
IEEE
14 years 7 days ago
A multi-agent based evolutionary algorithm in non-stationary environments
— In this paper, a multi-agent based evolutionary algorithm (MAEA) is introduced to solve dynamic optimization problems. The agents simulate living organism features and co-evolv...
Yang Yan, Hongfeng Wang, Dingwei Wang, Shengxiang ...
AEI
2005
99views more  AEI 2005»
13 years 5 months ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson