Krasnogor, N. (2002). Studies on the theory and design space of memetic algorithms. Doctoral dissertation, University of the West of England, Bristol, England. Home/Search Document Not in Database Summary Related Articles Check |
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Balance between Genetic Search and Local Search in.. - Ishibuchi, Yoshida.. (2002) (1 citation) (Correct)
....this paper in Section V where some topics for future research are also suggested. II. MOGLS ALGORITHMS The outline of our MOGLS can be written in a generic form as Fig. 4. This figure shows a basic structure of simple memetic algorithms. For other types of memetic algorithms, see Krasnogor [34] where taxonomy of memetic algorithms was given using an index number D. Our MOGLS is a 4 = D memetic algorithm in his taxonomy (for details, see [34] Initialization EMO Part Local Search Part Initial population New population Improved population Fig. 4 Generic form of our MOGLS. A. ....
....in a generic form as Fig. 4. This figure shows a basic structure of simple memetic algorithms. For other types of memetic algorithms, see Krasnogor [34] where taxonomy of memetic algorithms was given using an index number D. Our MOGLS is a 4 = D memetic algorithm in his taxonomy (for details, see [34]) Initialization EMO Part Local Search Part Initial population New population Improved population Fig. 4 Generic form of our MOGLS. A. Former MOGLS We explain the former MOGLS [20] 21] using the following N objective minimization problem: Minimize ) 2 1 x x x z ....
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N. Krasnogor, "Studies on the theory and design space of memetic algorithms," Ph. D. Thesis, University of the West of England, Bristol, June 2002.
Searching for Search Algorithms: Experiments in Meta-search - Ross (2002) (Correct)
....with mutation. With the single search set used in our searches, this would be a steady state genetic algorithm. Memetic crossover: 3 or more crossover operators are used, possibly in combination with mutation. The use of multiple crossovers from the search set is akin to a memetic search [9], in which a number of individuals in the search set contribute information to the next individual created. Repeated introduction of new information by multiple individuals via crossover has the statistical e#ect of introducing many instances of useful new information, while simultaneously ....
N. Krasnogor. Studies on the Theory and Design Space of Memetic Algorithms. PhD thesis, Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Bristol, 2002.
Toward Truly "Memetic" Memetic Algorithms: discussion and.. - Krasnogor, Gustafson (2002) Self-citation (Krasnogor) (Correct)
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N. Krasnogor. Studies on the Theory and Design Space of Memetic Algorithms. (Submitted). Ph.D. Thesis, Faculty of Engineering, Computer Science and Mathematics. University of the West of England, 2002.
Multimeme Algorithms for Protein Structure - Krasnogor, Blackburne, Burke.. (2002) Self-citation (Krasnogor) (Correct)
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N. Krasnogor. Studies on the Theory and Design Space of Memetic Algorithms. Ph.D. Thesis, Faculty of Computing, Mathematics and Engineering, University of the West of England, Bristol, United Kingdom, 2002.
Multimeme Algorithms for the Structure Prediction and.. - Krasnogor, Smith (2002) (1 citation) Self-citation (Krasnogor) (Correct)
....are evolutionary algorithms (EAs) that include, as part of the standard evolutionary cycle of crossover mutation selection, a local search stage. They have been extensively used and studied on a wide range of problems. Multimeme evolutionary algorithms (MMAs) were introduced in Krasnogor et al. [12, 9]. The distinction between memetic and multimeme algorithms is the use of a family of local searchers. An MA employs a single, usually complex, local search heuristic, while a MMA relies on a set of simple local searchers. In an MMA the representation of a solution in an individual is augmented ....
....rationale of adaptation to use appropriate heuristics for di erent problem instances, stages of the search or individuals in the population. MMAs were successfully applied to a dynamic version of OneMax, to the NK Landscapes and the TSP in [12] and to the two bioinformatics problems we use here in [9]. 2 Protein Structure Prediction Modern molecular biology has made it possible to determine and store huge amounts of information about DNA sequences, including the amino acid sequences of a diverse set of proteins. A protein is a chain of amino acid residues that folds into a speci c native ....
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N. Krasnogor. Studies on the Theory and Design Space of Memetic Algorithms. Ph.D. Thesis, Faculty of Engineering, Computer Science and Mathematics. University of the West of England. Bristol, United Kingdom. http://dirac.chem.nott.ac.uk/~natk/Public/, 2002.
Alignment of Protein Structures with a Memetic.. - Carr, Hart.. (2002) (1 citation) Self-citation (Krasnogor) (Correct)
....problem, the distances in the contact map are discretized to zero or one, depending on whether the pairwise distances between residues are within a speci ed threshold. Although this discretization would seem to be easier than aligning matrices with real values, the problem is in fact NPcomplete [4, 5, 9]. We have previously proposed a A protein s native state is associated with its minimal free energy con guration. The biological function of a protein is achieved in this state. rigorous approach to Max CMO [11] This approach employs an integer programming (IP) formulation for Max CMO, which is ....
....Programming (LP) relaxation of the IP to produce the upper bounds, and a Genetic Algorithm (GA) is used to provide lower bounds at the branch nodes. The aim of the present research is to investigate the use of more sophisticated evolutionary algorithms: Multimeme memetic evolutionary algorithms [9], which integrate multiple local search strategies with a standard evolutionary search. We employ the LP relaxation of the Max CMO IP to provide upper bounds on the quality of the alignment of two proteins structures, and thus we can empirically evaluate the quality of the solutions that we ....
[Article contains additional citation context not shown here]
N. Krasnogor. Studies on the Theory and Design Space of Memetic Algorithms. Ph.D. Thesis, Faculty of Engineering, Computer Science and Mathematics. University of the West of England. Bristol, United Kingdom. http://dirac.chem.nott.ac.uk/~natk/Public/, 2002.
Substructural Neighborhoods for Local Search in the.. - Fernando Lobo Medal (Correct)
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Krasnogor, N. (2002). Studies on the theory and design space of memetic algorithms. Doctoral dissertation, University of the West of England, Bristol, England.
Evolving Evolutionary Algorithms Using Linear Genetic Programming - Oltean (2005) (Correct)
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Krasnogor, N. (2002) Studies on the Theory and Design Space of Memetic Algorithms, PhD Thesis, University of the West of England, Bristol, 2002.
An Empirical Investigation on Memes, Self-generation - And Nurse Rostering (Correct)
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Krasnogor, N.: Studies on the Theory and Design Space of Memetic Algorithms, PhD Thesis, University of the West of England, Bristol, United Kingdom (2002)
Final Exam Scheduler - FES - Ozcan, Ersoy (2005) (Correct)
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Krasnogor, N. (2002) "Studies on the Theory and Design Space of Memetic Algorithms", PhD Thesis, University of the West of England, Bristol, United Kingdom.
An Analysis of Diversity in Genetic Programming - Gustafson (2004) (Correct)
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Krasnogor, N. (2002). Studies on the Theory and Design Space of Memetic Algorithms. PhD thesis, University of the West of England, Bristol, UK.
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