Genetic Algorithms and Fuzzy Multiobjective Optimization
Genetic Algorithms and Fuzzy Multiobjective Optimization
On set-based multiobjective optimization
IEEE Transactions on Evolutionary Computation
Analysis of the distribution of individuals in modified genetic algorithms
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
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The article presents the idea of the intelligent system for the multiobjective optimization. The system consists of the genetic algorithm (GA) and the fuzzy logic controller (FLC). In experiments we investigated the maintenance of genetic algorithms with the variable length of genes. The genes of individuals are encoded and represented by real numbers. The FLC controls the length of individuals' genotypes in the genetic algorithm. The variable length of the genotype of individuals allows for the limitation of the computational effort, when the length of the genotype of an individual grows smaller. We chose the problem of the distribution of Access Points in a given area in a wireless network as the test-function for our experiments. In the article we presented the results obtained during the optimization of the test-function. The experiments show, that the proposed system is an efficient tool for solving the multiobjective optimization problems. The proposed system can be used to solve similar problems of multiobjective optimization.