• Journal of Advanced Marine Engineering and Technology
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• 제33권3호
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• pp.403-410
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• 2009

The aim of this research is to develop the Bees Algorithm named 'the dynamic allocated Bees Algorithm' for multi-objective problem, especially in order to be suit for Pareto optimality. In addition two new neighbourhood search methods have been developed to produce enhanced solutions for a multi-objective problem named 'random selection neighbourhood search' and 'weighted sum neighbourhood search' and they were compared with the basic neighbourhood search in the dynamic allocated Bees Algorithm. They were successfully applied to an Environmental/Economic (electric power) dispatch (EED) problem and simulation results presented for the standard IEEE 30-bus system and they were compared to those obtained using other approaches. The comparison shows the superiority of the proposed dynamic allocated Bees Algorithms and confirms its suitability for solving the multi-objective EED problem.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제13권1호
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• pp.13-20
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• 2009

The IPSAP which is a finite element analysis program has been developed for high parallel performance computing. This program consists of various analysis modules - stress, vibration and thermal analysis module, etc. The M orthogonal block Lanczos algorithm with shiftinvert transformation is used for solving eigenvalue problems in the vibration module. And the multifrontal algorithm which is one of the most efficient direct linear equation solvers is applied to factorization and triangular system solving phases in this block Lanczos iteration routine. In this study, the performance enhancement procedures of the IPSAP are composed of the following stages: 1) communication volume minimization of the factorization phase by modifying parallel matrix subroutines. 2) idling time minimization in triangular system solving phase by partial inverse of the frontal matrix and the LCM (least common multiple) concept.

• 한국멀티미디어학회논문지
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• 제20권4호
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• pp.696-703
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• 2017

In this paper, we show how to design based on solving Sudoku problem that is one of the NP-complete problems like Go. We show how to use greedy method which can minimize depth based on tree expansion and how to apply heuristic algorithm for pruning unnecessary branches. As a result of measuring the performance of the proposed method for solving of Sudoku problems, this method can reduce the number of function call required for solving compared with the method of heuristic algorithm or recursive method, also this method is able to reduce the 46~64 depth rather than simply expanding the tree and is able to pruning unnecessary branches. Therefore, we could see that it can reduce the number of leaf nodes required for the calculation to 6 to 34.

• 한국과학교육학회지
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• 제40권4호
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• pp.385-398
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• 2020

본 연구에서는 서로 다른 학습접근방식의 학생이 유전 가계도 문제 해결 과정상에서 어떠한 차이를 보여주는지 심층적으로 들여다보고자 하였다. 연구 대상은 고등학교 2학년 학생으로 생명과학I을 이수한 학생으로 학업성취수준은 비슷하였으나 학습접근방식이 각각 심층적 접근방식과 피상적 접근방식을 나타내었다. 각 학생의 문제 해결 사례를 심층적으로 분석하기 위해 문제 해결 과정은 비디오 녹화되었고, 문제 해결이 종료된 후에 학생들의 문제 해결 과정에 대한 사고 구술 인터뷰를 실시하였다. 연구 결과, 학생들은 2가지 형질의 유전 원리가 불확실한 문제 상황을 해결하는 과정에서 유사한 오류를 보여주었다. 하지만 심층적 학습접근방식의 학생 A는 자발적으로 2번 반복하여 문제를 해결하면서 3가지 제한 요인에 대해 원리 기반추론을 하며 옳은 개념적 프레이밍을 나타내었다. 검토 단계에서 자료와 본인이 그린 가계도 사이의 일치도를 점검하고, 문제 해결 이후에도 끊임없이 본인의 문제 해결 과정을 점검하였다. 마지막의 문제 해결 과정에서는 성공적인 문제 해결 알고리즘에 근접한 문제 해결 과정을 나타내었다. 하지만 피상적 학습접근방식의 학생 B는 연구자의 권유로 비자발적으로 문제 해결 과정을 반복하였고, 답을 구하려는 목적 지향적인 문제 해결 태도로 인해 문제에서 제시한 일부 정보만을 검토하였다. 문제의 제한 요인에 대해 기억 장치 추론이나 임의적 추론을 통해서 옳지 않은 개념적 프레이밍을 하였고, 이를 수정하지 않고 유지하는 모습을 나타내었다. 본 연구 결과를 통해 심층적 접근방식과 피상적 접근방식의 학생이 문제 해결 과정에서 추론 방식과 개념적 프레이밍의 변화가 어떻게 일어나는지 구체적으로 살펴봄으로써 유전 문제의 접근을 어려워하는 학생들이나 이들을 지도하는 교사들에게 도움을 줄 수 있을 것이다.

• 대한안전경영과학회지
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• 제6권2호
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• pp.141-154
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• 2004

The objective of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the job shop scheduling. The proposed heuristic method is based on a constraint satisfaction problem technique and a improved randomizing search algorithm. In this paper, ILOG programming libraries are used to embody the job shop model, and a constraint satisfaction problem technique is developed for this model to generate the initial solution. Then, a improved randomizing search algorithm is employed to overcome the increased search time of constrained satisfaction problem technique on the increased problem size and to find a improved solution. Computational experiments on well known MT and LA problem instances show that this approach yields better results than the other procedures.

• 산업경영시스템학회지
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• 제42권1호
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• pp.8-20
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• 2019

The vehicle routing problem is one of the vibrant research problems for half a century. Many studies have extensively studied the vehicle routing problem in order to deal with practical decision-making issues in logistics. However, developments of new logistics strategies have inevitably required investigations on solution methods for solving the problem because of computational complexity and inherent constraints in the problem. For this reason, this paper suggests a simulated annealing (SA) algorithm for a variant of vehicle routing problem introduced by a previous study. The vehicle routing problem is a multi-depot and multi-trip vehicle routing problem with multiple heterogeneous vehicles restricted by the maximum permitted weight and the number of compartments. The SA algorithm generates an initial solution through a greedy-type algorithm and improves it using an enhanced SA procedure with three local search methods. A series of computational experiments are performed to evaluate the performance of the heuristic and several managerial findings are further discussed through scenario analyses. Experiment results show that the proposed SA algorithm can obtain good solutions within a reasonable computation time and scenario analyses show that a transportation system visiting non-dedicated factories shows better performance in truck management in terms of the numbers of vehicles used and trips for serving customer orders than another system visiting only dedicated factories.

• Nonlinear Functional Analysis and Applications
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• 제29권2호
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• pp.393-418
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• 2024

In this paper, we propose a new inertial subgradient extragradient algorithm with a new linesearch technique that combines the inertial subgradient extragradient algorithm and the KrasnoselskiiMann algorithm. Under some suitable conditions, we prove a weak convergence theorem of the proposed algorithm for finding a common element of the common solution set of a finitely many variational inequality problem and the fixed point set of a nonexpansive mapping in real Hilbert spaces. Moreover, using our main result, we derive some others involving systems of variational inequalities. Finally, we give some numerical examples to support our main result.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.191-194
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• 2003

Location-allocation problem is known as one of the important problem faced in Industrial Engineering and Operations Research fielde. There are many variations on this problem for different applications, however, most of them consider no obstacle existing. Since the location-allocation problem with obstacles is very complex and with many infeasible solutions, no direct method is effective to solve it. In this paper we propose a hybrid Genetic Algorithm (hGA) method for solving this problem. The proposed hGA is based on Lagrangian relaxation method and Dijkstra's shortest path algorithm. To enhance the proposed hGA, a Fuzzy Logic Controller (FLC) approach is also adopted to auto-tune the GA parameters.

• 한국경영과학회지
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• 제23권3호
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• pp.49-62
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• 1998

In the ring loading problem, traffic demands are given for each pair of nodes in an undirected ring network with n nodes and a flow is routed in either of the two directions, clockwise and counter-clockwise. The load of a link is the sum of the flows routed through the link and the objective of the Problem is to minimize the maximum load on the ring. In the ring loading problem with integer demand splitting, each demand can be split between the two directions and the flow routed in each direction is restricted to integers. Recently, Vachani et al. ［INFORMS J. Computing 8 (1996) 235-242］ have developed an Ο(n$^3$) algorithm for solving this integer version of the ring loading problem and independently, Schrijver et al. ［to appear in SIAM J. Disc. Math.］ have presented an algorithm which solves the problem with ｛0,1｝ demands in Ο（n$^2$｜K｜ ) time where K denotes the index set of the origin-desㅇtination pairs of nodes having flow demands. In this paper, we develop an algorithm which solves the problem in Ο(n ｜K｜) time.

• 대한수학회보
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• 제53권3호
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• pp.853-874
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• 2016

Based on a particular overlapping domain decomposition technique, a parallel finite element discretization algorithm for the generalized Stokes equations is proposed and investigated. In this algorithm, each processor computes a local approximate solution in its own subdomain by solving a global problem on a mesh that is fine around its own subdomain and coarse elsewhere, and hence avoids communication with other processors in the process of computations. This algorithm has low communication complexity. It only requires the application of an existing sequential solver on the global meshes associated with each subdomain, and hence can reuse existing sequential software. Numerical results are given to demonstrate the effectiveness of the parallel algorithm.