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» Competitive Self-adaptation in Evolutionary Algorithms
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CEC
2010
IEEE
13 years 2 months ago
Multi-objective robust static mapping of independent tasks on grids
We study the problem of efficiently allocating incoming independent tasks onto the resources of a Grid system. Typically, it is assumed that the estimated time to compute each task...
Bernabé Dorronsoro Díaz, Pascal Bouv...
GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
14 years 1 months ago
SNDL-MOEA: stored non-domination level MOEA
There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving MultiObjective Optimization (MOO) problems; two of the best are NSGA-II and -M...
Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilke...
GECCO
2009
Springer
125views Optimization» more  GECCO 2009»
14 years 8 days ago
Preserving population diversity for the multi-objective vehicle routing problem with time windows
The Vehicle Routing Problem’s main objective is to find the lowest-cost set of routes to deliver goods to customers, which have a service time window, using a fleet of identic...
Abel Garcia-Najera
ENC
2005
IEEE
14 years 1 months ago
Saving Evaluations in Differential Evolution for Constrained Optimization
Generally, evolutionary algorithms require a large number of evaluations of the objective function in order to obtain a good solution. This paper presents a simple approach to sav...
Efrén Mezura-Montes, Carlos A. Coello Coell...
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
13 years 11 months ago
Adaptive evolution: an efficient heuristic for global optimization
This paper presents a novel evolutionary approach to solve numerical optimization problems, called Adaptive Evolution (AEv). AEv is a new micro-population-like technique because i...
Francisco Viveros Jiménez, Efrén Mez...