• Journal of applied mathematics & informatics
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• 제42권1호
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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.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제16권1호
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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.

• 한국CDE학회논문집
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• 제9권1호
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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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• 제27권4호
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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).

• 정보관리학회지
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• 제10권1호
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• pp.53-63
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• 1993

AND와 OR에 대한 연삭식으로 MIN과 MAX를 사용하는 기존의 퍼지 집합 모델은 많은 경우에 사람이 생각하는 것과 다른 문서값을 생성하기 때문에 정보 검색 모델로서 부적합하다고 비판되어 왔다. 퍼지 집합 이론이 도입된 이후로 AND OR에 대한 연삭식으로 다양한 퍼지 연산자들이 개발되어 왔다. 본 논문에서는 이러한 퍼지 연산자들의 문서값 생성 특성을 분석하고, MIN과 MAX 대신에 긍정적 보상 연산자라 불리는 퍼지 연산자를 사용할 것을 제안한다. 긍정적 보상 연산자를 사용하는 퍼지 집합 모델이 보다 우수한 검색 효율을 제공함을 실험을 통하여 입증한다.

• 산업경영시스템학회지
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• 제20권41호
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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.

• 대한교통학회지
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• 제22권2호
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• pp.43-54
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• 2004

본 연구에서는 인공지능(Artificial Intelligence)방법 중의 하나인 유전자 알고리즘(Genetic Algorithm)을 도로선형최적화 모형개발의 탐색엔진으로 활용하기 위한 핵심도구인 유전자 연산자(Genetic Operator)의 개발과 적용과정을 통해 그 특징과 유용성을 제시하였다. 균일돌연변이 연산자, 직선돌연변이 연산자. 비균일 돌연변이 연산자, 전체 비균일 돌연변이 연산자 등 4개의 돌연변이 연산자가 탐색영역(Search space)의 가능한 모든 부분을 탐험(Exploration)하기 위해 적용되었으며, 단순교차 연산자, 두 개의 점을 이용한 교차 연산자, 산술교차 연산자, 학습교차 연산자 등 4개의 교차 연산자가 노선대안의 우수한 유전형질을 다음세대에 효과적으로 전달(Exploitation)하기 위해 시험되었다. 사례연구와 민감도 분석과정을 통해 유전자 알고리즘 및 개발 적용된 8개 유전자 연산자의 도로선형최적화과정 도입이 우수한 노선대안을 빠르고 효과적으로 탐색함을 알 수 있었으며, 돌연변이 연산자와 교차 연산자의 효과적 조합이 상호보완기능을 통해 탐색능력의 향상에 큰 영향을 끼치는 것으로 파악되었다. 또한, 개발 적용된 연산자 이외에도 새로운 연산자의 개발 가능성이 무한하며, 이는 도로선형최적화에 유전자 알고리즘의 적용이 타당함을 반증함도 주목할 만하다.

• 한국추진공학회지
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• 제3권1호
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• pp.55-64
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• 1999

대형 조선소에서는 선박에 사용하고 있는 수많은 부재들은 고가이고, 고급기술을 필요로 하는 WORK-STAT10N급에서 구동되는 선박전용프로그램 등에 의하여 부재생성 및 네스팅을 하고 있다. 그러나 중소형 조선소의 경제적, 기술적인 사정으로 고가의 장비와 고급인력의 확보가 어려운 실정이다. 따라서 본 연구에서는 널리 보급되어 있는 PC에서 사용 가능한 파라메트릭 매크로에 의한 부재생성과 부재의 네스팅 프로그램을 개발하였다.

• 경영과학
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• 제20권1호
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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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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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.