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AEI
2005
99views more  AEI 2005»
13 years 10 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
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
14 years 1 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
ATAL
2008
Springer
14 years 2 days ago
A best-first anytime algorithm for computing optimal coalition structures
This work presents a best-first anytime algorithm for computing optimal coalition structures. The approach is novel in that it generates coalition structures based on coalition va...
Chattrakul Sombattheera, Aditya Ghose
WSC
2007
14 years 12 days ago
Optimal scheduling of probabilistic repetitive projects using completed unit and genetic algorithms
In this paper we introduce the completed unit algorithm (CU-AL), a probabilistic scheduling methodology for repetitive projects. The algorithm has two main advantages, simplicity ...
Chachrist Srisuwanrat, Photios G. Ioannou
CEC
2007
IEEE
14 years 4 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...