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» Competitive Self-adaptation in Evolutionary Algorithms
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130
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CEC
2010
IEEE
14 years 10 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...
123
Voted
GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
15 years 9 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...
128
Voted
GECCO
2009
Springer
125views Optimization» more  GECCO 2009»
15 years 8 months 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
15 years 9 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...
116
Voted
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
15 years 7 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...