A Multiobjective Evolutionary-Simplex Hybrid Approach for the Optimization of Differential Equation Models of Gene Networks

This paper describes genetic and hybrid approaches for multiobjective optimization using a numerical measure called fuzzy dominance. Fuzzy dominance is used when implementing tournament selection within the genetic algorithm (GA). In the hybrid version, it is also used to carry out a Nelder-Mead sim...

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Vydané v:IEEE transactions on evolutionary computation Ročník 12; číslo 5; s. 572 - 590
Hlavní autori: Koduru, P., Zhanshan Dong, Das, S., Welch, S.M., Roe, J.L., Charbit, E.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.10.2008
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Applied sciences
Arabidopsis
Bioinformatics
Biological system modeling
Biology computing
Combinatorics
Combinatorics. Ordered structures
Computer networks
Computer science; control theory; systems
Data mining
Data processing. List processing. Character string processing
Differential equations
Exact sciences and technology
Flows in networks. Combinatorial problems
Fuzzy
fuzzy dominance
Genes
Genetic algorithms
genetic algorithms (GAs)
Genomics
Graph theory
hybrid algorithms
Information retrieval. Graph
Mathematical models
Mathematics
Memory organisation. Data processing
multiobjective optimization
Networks
Operational research and scientific management
Operational research. Management science
Optimization
Organisms
Oryza sativa
Parameter estimation
Sciences and techniques of general use
Searching
simplex
Software
Studies
Theoretical computing
Differential equation
Evolutionary algorithm
Biological model
Multiobjective programming
simplex
Information extraction
Network management
Data mining
Combinatorial optimization
Modeling
Convergence
multiobjective optimization
fuzzy dominance
Genetics
genomics
hybrid algorithms
Bioinformatics
Local search
Data analysis
Pareto optimum
Biological system modeling
Dominance
Data processing
Graph theory
Biological system
Fuzzy logic
Genetic algorithm
Simplex method
genetic algorithms (GAs)
Genome
Tournament
ISSN:1089-778X, 1941-0026
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Shrnutí:This paper describes genetic and hybrid approaches for multiobjective optimization using a numerical measure called fuzzy dominance. Fuzzy dominance is used when implementing tournament selection within the genetic algorithm (GA). In the hybrid version, it is also used to carry out a Nelder-Mead simplex-based local search. The proposed GA is shown to perform better than NSGA-II and SPEA-2 on standard benchmarks, as well as for the optimization of a genetic model for flowering time control in rice. Adding the local search achieves faster convergence, an important feature in computationally intensive optimization of gene networks. The hybrid version also compares well with ParEGO on a few other benchmarks. The proposed hybrid algorithm is then applied to estimate the parameters of an elaborate gene network model of flowering time control in Arabidopsis. Overall solution quality is quite good by biological standards. Tradeoffs are discussed between accuracy in gene activity levels versus in the plant traits that they influence. These tradeoffs suggest that data mining the Pareto front may be useful in bioinformatics.
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ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2008.917202