• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2325-2330
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• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.

• 한국인터넷방송통신학회논문지
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• 제14권3호
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• pp.191-198
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• 2014

본 논문은 복잡한 비평활 발전비용함수를 가진 경제급전의 최적화 문제를 풀기 위해 단순히 선형 근사함수를 이용하는 방법을 제안하였다. 제안된 알고리즘은 비평활 발전비용 함수를 선형으로 근사시키고, 요구량이 현재의 발전량을 초과하는 경우 발전단가가 비싼 발전기의 가동을 중지시키고, 발전단가가 보다 큰 발전기의 발전량을 감소시켜 요구량과 발전량의 균형을 맞추는 개념을 도입하였다. 경제급전 문제의 시험사례로 빈번히 활용되고 있는 데이터에 대해 제안된 알고리즘을 적용한 결과 기존의 휴리스틱 알고리즘의 최적화 해를 획기적으로 감소시킬 수 있었으며, 현재 실무적으로 적용되고 있는 2차 평활함수 근사법과 유사한 결과를 얻었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.823-828
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• 1992

A novel steepest descent adaptive filter algorithm, which uses the instantaneous stochastic gradient for the steepest descent direction, is derived from a newly devised performance index function. The performance function for the new algorithm is improved from that for the LMS in consideration that the stochastic steepest descent method is utilized to minimize the performance index iterativly. Through mathematical analysis and computer simulations, it is verified that there are substantial improvements in convergence and misadjustments even though the computational simplicity and the robustness of the LMS algorithm are hardly sacrificed. On the other hand, the new algorithm can be interpreted as a variable step size adaptive filter, and in this respect a heuristic method is proposed in order to reduce the noise caused by the step size fluctuation.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.825-835
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• 2017

Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

• Journal of the Korean Statistical Society
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• 제11권2호
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• pp.88-93
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• 1982

A local limit theorem for large deviations for the i.i.d. random variables was given by Richter (1957), who used the saddle point method of complex variables to prove it. In this paper we give an alternative form of local limit theorem for large deviations for the i.i.d. random variables which is essentially equivalent to that of Richter. We prove the theorem by more direct and heuristic method under a rather simple condition on the moment generating function (m.g.f.). The theorem is proved without assuming that $E(X_i)=0$.

• 산업경영시스템학회지
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• 제16권27호
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• pp.91-104
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• 1993

This paper is concerned with flow shop scheduling problems having the common due date. V-shape property is used for algorithms with early and tardy penalty cost. The objective of this paper is developing efficient heuristic scheduling algorithms for minimizing total penalty cost function and determining the optimal common due date. The between job delay and the work in process are considered for developing algorithms as penalty cost. Algorithms is simulated to analyze interrelated factors. A numerical example is given for illustrating the proposed algorithms.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1998년도 추계학술대회 논문집
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• pp.216-219
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• 1998

This study proposes JPT(Job-Pair Tardiness) that choose operation to be expected to generate better schedule consequence in comparing schedulable operation sets in pair to minimize total tardiness evaluation function in performing scheduling. In result of comparison with existing assignment rules. JPT generates better solution than most other rules in all kinds of problems. So it is anticipated that this is used for initial solution of heuristic and is used for finding more improved solution.

• 한국경영과학회지
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• 제15권2호
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• pp.1-15
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• 1990

A mathematical definition of the cluster is suggested. A nonlinear 0-1 integer programming formulation for the multi-dimensional entity clustering problem is developed. A heuristic method named MDEC (Multi-Dimensional Entity Clustering) using centroids and the binary partition is developed and the numerical examples are shown. This method has an advantage of providing bottle-neck entity informations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.1106-1108
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• 1997

This paper presents a new approach on genetic algorithms to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through combination in penalty function with death penalty, generation-apart elitism, atavism and heuristic crossover. Numerical results on an actual utility system consisted of 13 thermal units show that the proposed approach is faster and robuster than classical genetic algorithm.

• 산업융합연구
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• 제5권2호
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• pp.21-32
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• 2007

This paper deals with the sequencing problem in the operation of the manufacturing systems with the constraint of buffer capacity. Some of studies for this theme have been progressed for several years. And then most of them considered only one objective, such as maximum lateness, machine utilization, makespan, mean flowtime and so on. This study deal with two objectives of the delivery for customers and the idle time of machines for producers. For the decision of sequence, the utility function is used. The developed heuristic algorithm presents a good solution. Through a numerical example, the procedures of the job sequencing is explained.