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» Design Issues in a Multiobjective Cellular Genetic Algorithm
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GECCO
2004
Springer
112views Optimization» more  GECCO 2004»
13 years 10 months ago
Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization
This paper discusses the implementation of local search in evolutionary multiobjective optimization (EMO) algorithms for the design of a simple but powerful memetic EMO algorithm. ...
Hisao Ishibuchi, Kaname Narukawa
EGC
2005
Springer
13 years 11 months ago
A Service Oriented Architecture for Decision Making in Engineering Design
Abstract. Decision making in engineering design can be effectively addressed by using genetic algorithms to solve multi-objective problems. These multi-objective genetic algorithm...
Alex Shenfield, Peter J. Fleming
GECCO
2008
Springer
157views Optimization» more  GECCO 2008»
13 years 6 months ago
Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata
Self-adaptation is used a lot in Evolutionary Strategies and with great success, yet for some reason it is not the mutation adaptation of choice for Genetic Algorithms. This poste...
Ron Breukelaar, Thomas Bäck
TR
2008
78views more  TR 2008»
13 years 5 months ago
MOMS-GA: A Multi-Objective Multi-State Genetic Algorithm for System Reliability Optimization Design Problems
A custom genetic algorithm was developed and implemented to solve multiple objective multi-state reliability optimization design problems. Many real-world engineering design proble...
Heidi A. Taboada, Jose F. Espiritu, David W. Coit
EC
2002
228views ECommerce» more  EC 2002»
13 years 5 months ago
Improved Sampling of the Pareto-Front in Multiobjective Genetic Optimizations by Steady-State Evolution: A Pareto Converging Gen
Previous work on multiobjective genetic algorithms has been focused on preventing genetic drift and the issue of convergence has been given little attention. In this paper, we pre...
Rajeev Kumar, Peter Rockett