• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.65-76
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• 2024

In this paper, the I-transform of the Mellin convolution type is presented. Based on the Mellin transform theory, a general integral transform of the Mellin convolution type is introduced. The generating operators for I-transform together with the corresponding operational relations are also presented.

• The Pure and Applied Mathematics
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• v.16 no.1
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• pp.147-154
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• 2009

Tamanoi proposed higher Schwarzian operators which include the classical Schwarzian derivative as the first nontrivial operator. In view of the relations between the classical Schwarzian derivative and the analogous differential operator defined in terms of Peschl's differential operators, we define the generating function of our generalized higher operators in terms of Peschl's differential operators and obtain recursion formulas for them. Our generalized higher operators include the analogous differential operator to the classical Schwarzian derivative. A special case of our generalized higher Schwarzian operators turns out to be the Tamanoi's operators as expected.

• Korean Journal of Computational Design and Engineering
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• v.9 no.1
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• pp.27-34
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• 2004

A tetrahedral mesh generation scheme using 3-D operators has been presented. The proposed scheme employs new 3-D operators such as rearranging and modified finishing operators in addition to the previous trimming, wedging, digging, splitting and finishing operators. These new operators have been introduced in order to increase the stability of mesh generation process. Check processings with surrounded element edges and faces have also been optimized by employing a searching algorithm. Sample meshes are constructed to demonstrate the mesh generating capability of the proposed algorithm.

• Nonlinear Functional Analysis and Applications
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• v.27 no.4
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• pp.813-837
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• 2022

In this paper we consider inverse problem for a general class of nonlinear stochastic differential equations on Hilbert spaces whose generating operators (drift, diffusion and jump kernels) are unknown. We introduce a class of function spaces and put a suitable topology on such spaces and prove existence of optimal generating operators from these spaces. We present also necessary conditions of optimality including an algorithm and its convergence whereby one can construct the optimal generators (drift, diffusion and jump kernel).

• Journal of the Korean Society for information Management
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• v.10 no.1
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• pp.53-63
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• 1993

The conventional fuzzy set model has been criticized as a retrieval model because the MIN and MAX operators have the properties adverse to effective calculation of document values. Since the first introduction of fuzzy set theory a variety of fuzzy operators have been developed, which can replace the MIN and MAX operators. We analyze their behavioral aspects of generating document values, and propose the enhanced fuzzy set model based on a class of fuzzy operators called positively compensatory operators. We also show through performance experiments that the proposed fuzzy set model provides higher retrieval effectiveness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.1-14
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• 1997

This study proposes a genetic algorithm using Pr(equation omitted)fer number for the traveling salesman problem(PNGATSP). Nearest neighbor nodes are mixed with randomly selected nodes at the stage of generating initial solutions. Proposed PNGATSP adopts a few ideas which are different from traditional genetic algorithms. For instance, an exponential fitness function and elitism are used and Pr(equation omitted)fer number is used for encoding TSP. Genetic operators are selected by experiments, which make a good solution among four combinations of conventional genetic operators and new genetic operators. For respective combinations, robust set of parameters is determined by the experimental designing approach. The feature of Pr(equation omitted)fer number code for TSP and the search power of GA using Pr(equation omitted)fer number is analysed. The best is a combination of OX(order crossover) and swap, which is superior to the other experimented combinations of genetic operators by 1.0%∼12.8% deviation.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.43-54
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• 2004

This study analyzes characteristics and applicability of genetic algorithms and genetic operators to optimize highway alignments. Genetic algorithms, one of artificial intelligence techniques, are fast and efficient search algorithms for generating, evaluation and finding optimal highway alignment alternatives. The performance of genetic algorithms as an optimal search tool highly depends on genetic operators that are designed as a problem-specific. This study adopts low mutation operators(uniform mutation operator, straight mutation operator, non-uniform mutation operator whole non-uniform mutation operator) to explore whole search spaces, and four crossover operators(simple crossover operator, two-point crossover operator, arithmetic crossover operator, heuristic crossover operator) to exploit food characteristics of the best chromosome in previous generations. A case study and a sensitivity analysis have shown that the eight problem-specific operators developed for optimizing highway alignments enhance the search performance of genetic algorithms, and find good solutions(highway alignment alternatives). It has been also found that a mixed and well-combined use of mutation and crossover operators is very important to balance between pre-matured solutions when employing more crossover operators and more computation time when adopting more mutation operators.

• Journal of the Korean Society of Propulsion Engineers
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• v.3 no.1
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• pp.55-64
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• 1999

Large size shipyards have peformed the generating of piece and the nesting using shipbuilding-oriented CAD program, which requires higher skilled operators and lots of costs. So, medium and small size shipyards have pursued different types of piece generation and nesting (arrangement method). This research is to develop a program for the generating of pieces with parametric macro method and a STRIP program for the nesting of pieces by PC, which can be applied in such shipyards.

• Korean Management Science Review
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• v.20 no.1
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• pp.51-64
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• 2003

The JSSP (Job Shop Scheduling Problem) Is one of the most general and difficult of all traditional scheduling problems. The goal of this research is to develop an efficient scheduling method based on genetic algorithm to address JSSP. we design scheduling method based on SGA (Single Genetic Algorithm) and PGA (Parallel Genetic Algorithm). In the scheduling method, the representation, which encodes the job number, is made to be always feasible, initial population is generated through integrating representation and G&T algorithm, the new genetic operators and selection method are designed to better transmit the temporal relationships in the chromosome, and island model PGA are proposed. The scheduling method based on genetic algorithm are tested on five standard benchmark JSSPs. The results were compared with other proposed approaches. Compared to traditional genetic algorithm, the proposed approach yields significant improvement at a solution. The superior results indicate the successful Incorporation of generating method of initial population into the genetic operators.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.338-341
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• 2005

In this paper, we present analytic forms of the ordered weighted averaging (OWA) operator weighting functions, each of which has properties of rank-based weights and a constant level of orness, irrespective of the number of objectives considered. These analytic forms provide significant advantages for generating OWA weights over previously reported methods. First, OWA weights can be efficiently generated by use of proposed weighting functions without solving a complicated mathematical program. Moreover, convex combinations of these specific OWA operators can be used to generate OWA operators with any predefined values of orness once specific values of orness are α priori stated by decision maker. Those weights have a property of constant level of orness as well. Finally, OWA weights generated at a predefined value of orness make almost no numerical difference with maximum entropy OWA weights in terms of dispersion.