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Genetic Algorithm With Species And Sexual Selection
2006 IEEE Conference on Cybernetics and Intelligent Systems, 2006In this paper we have proposed new real coded genetic algorithm with species and sexual selection (GAS3). GAS3 is a distributed quasi steady-state real-coded genetic algorithm. GAS3 uses sex determination method (SDM) to determine the sex (male or female) of members in population.
O. G. Kakde, Mukesh M. Raghuwanshi
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Vendor selection using genetic algorithm
The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 2012Selecting the right vendor is a complex business decision due to a huge number of competing vendors with a large number of complex criteria. The organization will suffer in the long run if vendors are not chosen wisely. Under multi criteria decision making, an algorithm, named VSFI, based on fuzzy clustering was proposed to select the most optimal ...
Shaila Sharmeen +4 more
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Selection Analysis in Genetic Algorithms
1998This paper describes a formal framework for the analysis of genetic algorithms. The model is based on the idea that over the space of populations an equivalence relation can be defined, as well as a metric on the space of equivalence classes induced by this relation.
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A Genetic Algorithm for the Index Selection Problem
2003This paper considers the problem of minimizing the response time for a given database workload by a proper choice of indexes. This problem is NP-hard and known in the literature as the Index Selection Problem (ISP). We propose a genetic algorithm (GA) for solving the ISP.
Dušan Tošić +2 more
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A thermodynamical selection rule for the genetic algorithm
Proceedings of 1995 IEEE International Conference on Evolutionary Computation, 2002The genetic algorithrri (GX), an optiriiizatioii tcchriiqiic bascd OII tlie proccss of cl-olutioii, suffers from a phenorrienon called prcrriature coiiwrgciicc. Tlia: is. the spstciri oftcii loses diversity of the population at ail earl?- stage of scarchirig. Iri this paper.
J. Yoshida +3 more
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Selective breeding in a multiobjective genetic algorithm
1998This paper describes an investigation of the efficacy of various elitist selection strategies in a multiobjective Genetic Algorithm implementation, with parents being selected both from the current population and from the archive record of nondominated solutions encountered during search.
I. Miller, Geoffrey T. Parks
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Genetic programming as a feature selection algorithm
2014 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2014Genetic Programming (GP) is an Evolutionary Algorithm commonly used to evolve computer programs in order to solve a particular task. Therefore, GP has been used to tackle different problems like classification and regression. In this work, the capabilities of GP in other types of problems are explored, particularly the feature selection problem.
Jose Maria Valencia-Ramirez +2 more
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Genetic algorithm attributes for component selection
Research in Engineering Design, 1996This paper uses a genetic algorithm for component selection given a user-defined system layout, a database of components, and a defined set of design specifications. A genetic algorithm is a search method based on the principles of natural selection. An introduction to genetic algorithms is presented, and genetic algorithm attributes that are useful ...
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Genetic algorithms in controller structure selection
1st International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA), 1995The selection of an appropriate set of manipulated variables to control a set of specified outputs is an important aspect of MIMO system design. This paper details how genetic algorithms may be used to provide an automated optimisation procedure for the selection of the input-output pairings based upon the Relative Gain Array (RGA).
I.G. French, C.S. Cox, C. K. S. Ho
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Probabilistic selection in cellular genetic algorithm
2012 8th International Conference on Natural Computation, 2012In this paper, we introduce a new selection operator, namely, a Probabilistic Selection operator which allows us to control the selection pressure in cellular genetic algorithms through reducing the effective neighborhood radius. One advantage for having probabilistic selection is that, once we have our probability density function in hand, we can ...
Teong-Joo Ong +2 more
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