• Journal of Information Processing Systems
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• 제13권5호
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• pp.1089-1102
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• 2017

In software systems, it has been observed that a fault is often caused by an interaction between a small number of input parameters. Even for moderately sized software systems, exhaustive testing is practically impossible to achieve. This is either due to time or cost constraints. Combinatorial (t-way) testing provides a technique to select a subset of exhaustive test cases covering all of the t-way interactions, without much of a loss to the fault detection capability. In this paper, an approach is proposed to generate 2-way (pairwise) test sets using genetic algorithms. The performance of the algorithm is improved by creating an initial solution using the overlap coefficient (a similarity matrix). Two mutation strategies have also been modified to improve their efficiency. Furthermore, the mutation operator is improved by using a combination of three mutation strategies. A comparative survey of the techniques to generate t-way test sets using genetic algorithms was also conducted. It has been shown experimentally that the proposed approach generates faster results by achieving higher percentage coverage in a fewer number of generations. Additionally, the size of the mixed covering arrays was reduced in one of the six benchmark problems examined.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2004년도 추계학술대회
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• pp.171-178
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• 2004

This study suggests a general paradigm enhancing genetic mutability. Mutability among heterogeneous members in a genetic population has been a major problem in application of genetic programming to diverse business problems. This suggested paradigm is implemented to developing new methods from existing methods. Within the evolutionary approach taken to designing new methods, a general representation scheme of the genetic programming framework, called a kernel, is introduced. The kernel is derived from the literature of algorithms and heuristics for combinatorial optimization problems. The commonality and differences among these methods have been identified and again combined by following the genetic inheritance merging them. The kernel was tested for selected methods in combinatorial optimization. It not only duplicates the methods in the literature, it also confirms that each of the possible solutions from the genetic mutation is in a valid form, a running program. This evolutionary method suggests diverse hybrid methods in the form of complete programs through evolutionary processes. It finally summarizes its findings from genetic simulation with insight.

• Biotechnology and Bioprocess Engineering:BBE
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• 제7권5호
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• pp.311-315
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• 2002

By the in vitro combinatorial mutagenesis, which is a sequential reaction of PCR mutagenesis and in vitro coupled transcription/translation with Escherichia coli S30 extract, S65 and E222 of green fluorescent protein of Aequarea victoria were comprehensively changed to all possible combinations of amino acids, thus totally 400 mutant (including a wild type) proteins were simultaneously produced and their fluorescent properties were analyzed. Although a few mutations had been reported so far at the 222nd position, replacement E222 to all other19 amino acids gave fluorescent signal to the mutants by changing Ser 65 to Ala together. Among the mutants, replacement to G, A, S, Q, H and C gave relatively high fluorescence. The in vitro combinatorial mutagenesis, therefore, has been proved valuable for comprehensive structure-function studies of proteins.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.12-22
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• 2024

The travelling salesman problem is very famous and very difficult combinatorial optimization problem that has several applications in operations research, computer science and industrial engineering. As the problem is difficult, finding its optimal solution is computationally very difficult. Thus, several researchers have developed heuristic/metaheuristic algorithms for finding heuristic solutions to the problem instances. In this present study, a new hybrid genetic algorithm (HGA) is suggested to find heuristic solution to the problem. In our HGA we used comprehensive sequential constructive crossover, adaptive mutation, 2-opt search and a new local search algorithm along with a replacement method, then executed our HGA on some standard TSPLIB problem instances, and finally, we compared our HGA with simple genetic algorithm and an existing state-of-the-art method. The experimental studies show the effectiveness of our proposed HGA for the problem.

• 한국미생물생명공학회:학술대회논문집
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• 한국미생물생명공학회 2002년도 학술발표대회
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• pp.18-25
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• 2002

The pikromycin biosynthetic system in Streptomyces venezuleae is unique for its ability to produce two groups of antibiotics that include the 12-membered ring macrolides methymycin and neomethymycin, and the 14-membered ring macrolides narbomycin and pikromycin. The metabolic pathway also contains two post polyketide-modification enzymes, a glycosyltransferase and P450 hydroxylase that have unusually broad substrate specificities. In order to explore further the substrate flexibility of these enzymes a series of hybrid polyketide synthases were constructed and their metabolic products characterized. The plasmid-based replacement of the multifunctional protein subunits of the pikromycin PKS in S. venezuelae by the corresponding subunits from heterologous modular PKSs resulted in recombinant strains that produce both 12- and 14-membered ring macrolactones with predicted structural alterations. In all cases, novel macrolactones were produced and further modified by the DesVII glycosyltransferase and PikC hydroxylase leading to biologically active macrolide structures. These results demonstrate that hybrid PKSs in S. venezuelae can produce a multiplicity of new macrolactones that are modified further by the highly flexible DesVII glycosyltransferase and PikC hydroxylase tailoring enzymes. This work demonstrates the unique capacity of the S. venezuelae pikromycin pathway to expand the toolbox of combinatorial biosynthesis and to accelerate the creation of novel biologically active natural products. The polyketide backbone of rifamycin B is assembled through successive condensation and ${\beta}$-carbonyl processing of the extender units by the modular rifamycin PKS. The eighth module, in the RifD protein, contains nonfunctional DH domain and functional KR domain, which specify the reduction of the ${\beta}$-carbonyl group resulting in the C-21 bydroxyl of rifamycin B. A four amino acid substitution and one amino acid deletion were introduced in the putative NADPH binding motif in the proposed KR domain encoded by rifD. This strategy of mutation was based on the amino acid sequences of the corresponding motif of the KR domain of module 3 in the RifA protein, which is believed dysfunctional, so as to introduce a minimum alteration and retain the reading frame intact, yet ensure loss of function. The resulting strain produces linear polyketides, from tetraketide to octaketide, which are also produced by a rifD disrupted mutant as a consequence of premature termination of polyketide assembly. Much of the structural diversity within the polyketide superfamily of natural products is due to the ability of PKSs to vary the reduction level of every other alternate carbon atom in the backbone. Thus, the ability to introduce heterologous reductive segments such as ketoreductase (KR), dehydratase (DH), and enoylreductase (ER) into modules that naturally lack these activities would increase the power of the combinatorial biosynthetic toolbox. The dehydratase domain of module 7 of the rifamycin PKS, which is predicted to be nonfunctional in view of the sequence of the apparent active site, was replaced with its functional homolog from module 7 of rapamycin-producing polyketide synthase. The resulting mutant strain behaved like a rifC disrupted mutant, i.e., it accumulated the heptaketide intermediate and its precursors. This result points out a major difficulty we have encountered with all the Amycolatopsis mediterranei strain containing hybrid polyketide synthases: all the engineered strains prepared so far accumulate a plethora of products derived from the polyketide chain assembly intermediates as major products instead of just analogs of rifamycin B or its ansamycin precursors.

• Genomics & Informatics
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• 제6권4호
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• pp.166-172
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• 2008

A multitude of protein-coding sequence variations (CVs) in the human genome have been revealed as a result of major initiatives, including the Human Variome Project, the 1000 Genomes Project, and the International Cancer Genome Consortium. This naturally has led to debate over how to accurately assess the functional consequences of CVs, because predicting the functional effects of CVs and their relevance to disease phenotypes is becoming increasingly important. This article surveys and compares variation databases and in silico prediction programs that assess the effects of CVs on protein function. We also introduce a combinatorial approach that uses machine learning algorithms to improve prediction performance.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.646-651
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• 1998

Fuzzy control has been used successfully in many practical applications. In traditional methods, experience and control knowledge of human experts are needed to design fuzzy controllers. However, it takes much time and cost. In this paper, an automatic design method for fuzzy controllers using genetic algorithms is proposed. In the method, we proposed an effective encoding scheme and new genetic operators. The maximum number of linguistic terms is restricted to reduce the number of combinatorial fuzzy rules in the research space. The proposed genetic operators maintain the correspondency between membership functions and control rules. The proposed method is applied to a cart centering problem. The result of the experiment has been satisfactory compared with other design methods using genetic algorithms.

• Structural Engineering and Mechanics
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• 제43권6호
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• pp.771-794
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• 2012

This paper presents a multi-objective evolutionary algorithm for combinatorial optimisation and applied for design optimisation of fiber reinforced composite structures. The proposed algorithm closely follows the implementation of Pareto Archive Evolutionary strategy (PAES) proposed in the literature. The modifications suggested include a customized neighbourhood search algorithm in place of mutation operator to improve intensification mechanism and a cross over operator to improve diversification mechanism. Further, an external archive is maintained to collect the historical Pareto optimal solutions. The design constraints are handled in this paper by treating them as additional objectives. Numerical studies have been carried out by solving a hybrid fiber reinforced laminate composite cylindrical shell, stiffened composite cylindrical shell and pressure vessel with varied number of design objectives. The studies presented in this paper clearly indicate that well spread Pareto optimal solutions can be obtained employing the proposed algorithm.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.365-370
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• 2001

The genetic algorithm that simulates the virus evolutionary theory has been developed applying to combinatorial optimization problems. The algorithm in this study uses only one individual and a population of viruses. The individual is attacked, inflected and improved by the viruses. The viruses are composed of flour genes (a pair of top gene and a pair of tail gene). If the individual is improved by the attacking, the inflection occurs. After the infection, the tail genes are mutated. If the same virus attacks several times and fails to inflect, the top genes of the virus are mutated. By this mutation, the individual can be improved effectively. In addition, the influence of the immunologic mechanism on evolution is simulated.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1123-1125
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• 1999

This paper proposes an optimization technique using Genetic Algorithm(GA) for service restoration in the distribution system. Restoration planning problem can be treated as a combinatorial optimization problem. So GA is appropriate to solve the service restoration problem in the distribution network. But searching capabilities of the GA can be enhanced by developing relevant repairing operation and modifying GA operations. In this paper, we aimed at finding appropriate open sectionalizing switch position for the restoration of distribution networks after disturbances using enhanced GA with repairing operation and modified mutation. Simulation results show that proposed method found the open sectionalizing switches with less out of service area and minimize transmission line losses and voltage drop.