• 한국정보처리학회논문지
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• 제4권10호
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• pp.2470-2476
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• 1997

본 연구에서는 실시간 휴리스틱 탐색 알고리즘을 개발하고 이것을 기존의 mini-min lookahead 알고리즘과 비교하였다. 많은 실시간 휴리스틱 탐색의 접근 방법에서 종종 전체 문제를 몇 개의 부 문제로 문제를 분할한다. 본 연구에서는 분할된 부 문제에서 마감시간을 적용할 뿐만 아니라 전체 해를 구하는데 있어서도 마감시간을 적용하는 알고리즘을 제안한다. 실시간 휴리스틱 탐색 알고리즘으로 제안된 $RTA^{\ast}$, SARTS, DYNORA 등의 알고리즘들은 탐색에 필요한 시간의 예측을 휴리스틱 평가 함수로부터 얻기 때문에 휴리스틱 평가의 정확도가 그 알고리즘의 성능을 보장하게 된다. 그러나 실세계의 문제에서 정확한 휴리스틱 평가 함수를 구하는 것은 매우 어려운 일이므로 부 문제 공간에서의 탐색 상황을 반영한 마감시간을 적용할 필요가 있다. 본 연구에서는 동적 마감시간 전략인 cut-off 방법을 사용하는 새로운 알고리즘을 제안한다.

• 한국해양공학회지
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• 제26권4호
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• pp.8-14
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• 2012

Two dimensional nesting is a common problem in industries such as the shipbuilding, automotive, clothing, shoe-making, and furniture industries, in which various parts are cut off from stock or packed in a flat space while minimizing waste or unoccupied space. Nesting is known as an NP-complete problem, which has a solution time proportional to the superpolynomial of the input size. It becomes practically impossible to find an optimal solution using algorithmic methods as the number of shapes to nest increases. Therefore, heuristic methods are commonly used to solve nesting problems. This paper presents an expert system that uses a heuristic search method based on an evaluation function for nesting problems, in which parts and stock are represented by pixels. The system is developed in CLIPS, an expert system shell, and is applied to four different kinds of example problems to verify its applicability in practical problems.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권5호
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• pp.283-289
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• 2003

This paper proposes an expert system which can determine automatically the shunting routes corresponding to the given shunting works by considering totally the train operating environments in the station. The expert system proposes the multiple shunting routes with priority of selection based on heuristic search strategy. Accordingly, system operator can select a shunting route with the safety and efficiency among the those shunting routes. The expert system consists of a main inference engine and a sub inference engine. The main inference engine determines the shunting routes with selection priority using the segment routes obtained from the sub inference engine. The heuristic rules are extracted from operating knowledges of the veteran route operator and station topology. It is implemented in C computer language for the purpose of the implementation of the inference engine using the dynamic memory allocation technique. And, the validity of the builted expert system is proved by a test case for the model station.

• 대한안전경영과학회지
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• 제11권3호
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• pp.157-166
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• 2009

In this study, we developed a heuristic algorithm to get better efficiency of clustering than conventional algorithms. Conventional clustering algorithm had lower efficiency of clustering as there were no solid method for selecting initial center of cluster and as they had difficulty in search solution for clustering. EMC(Expanded Moving Center) heuristic algorithm was suggested to clear the problem of low efficiency in clustering. We developed algorithm to select initial center of cluster and search solution systematically in clustering. Experiments of clustering are performed to evaluate performance of EMC heuristic algorithm. Squared-error of EMC heuristic algorithm showed better performance for real case study and improved greatly with increase of cluster number than the other ones.

• 대한전기학회논문지
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• 제40권2호
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• pp.135-143
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• 1991

The setting problem of protective devices in power distribution systems is a combinatorial search problem involving a lot of trial & errors to search for a proper solution which has a great impact for the system reliability. This paper discusses the nature of the problem and proposes a scheme to prune the decision tree achieving the efficient search for a setting solution by applying heuristic rules which utilize pattern informations of backup and primary devices. Its effectiveness is demonstrated through many tests on real systems.

• 대한건축학회논문집:구조계
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• 제33권12호
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• pp.53-62
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• 2017

Many gradient-based mathematical methods have been developed and are in use for structural size optimization problems, in which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. The main objective of this paper is to propose an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm that is derived using penalty function. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. In this paper, a discrete search strategy using the HS algorithm with a static penalty function is presented in detail and its applicability using several standard truss examples is discussed. The numerical results reveal that the HS algorithm with the static penalty function proposed in this study is a powerful search and design optimization technique for structures with discrete-sized members.

• 대한기계학회논문집A
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• 제22권1호
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• pp.90-101
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• 1998

This paper presents a scheduling method that uses Petri net modeling and heuristic search to handle the tool setup. In manufacturing systems, a tool is attached to a particular machine to process a particular operation. The activity to attach a tool to a particular machine and detach the tool from the machine requires time. The processing time of operations varies according to the attached tool and the machine used. The method proposed in this paper uses Petri net to model these characteristics and applies a search algorithm to the reachability graph of the Petri net model to generate an optimal or near-optimal schedule. New heuristic functions are developed for efficient search. The experimental results that show the effectiveness of the proposed method are presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.609-614
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• 1989

A collision avoidance algorithm based on a heuristic graph search and subgoals is presented. The joint angle space is quantized into cells. The evaluation function for a heuristic search is defined by the sum of the distance between the links of a manipulator and middle planes among the obstables and the distance between the end-effector and the subgoals on desired trajectory. These subgoals reduce the combinatorial explosion in the search space. This method enables us to avoid a dead-lock in searching. Its effectiveness has been verified by simulation studies.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1991년도 춘계공동학술대회 발표논문 및 초록집; 전북대학교, 전주; 26-27 Apr. 1991
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• pp.281-281
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• 1991

• 정보처리학회논문지B
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• 제15B권2호
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• pp.159-170
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• 2008

최근 들어 로봇 작업 계획기에 요구되는 중요한 기능 중의 하나가 이미 존재하는 컴포넌트 서비스들을 결합하여 새로운 서비스로 조합해낼 수 있는 계획 기능이다. 본 논문에서는 이러한 컴포넌트 서비스 조합을 위한 커널모듈로 개발된 휴리스틱 탐색 계획기인 JPLAN의 설계와 구현에 대해 설명한다. JPLAN은 효율적인 상태 공간 탐색을 위해 지역 탐색 알고리즘과 계획 그래프 휴리스틱을 이용한다. 본 논문에서 제안하는 지역 탐색 알고리즘인 EHC+는 FF 등의 상태 공간 계획기에 적용되어 높은 효율성을 보인 Enforced Hill-Climbing (EHC)을 확장한 것이다. EHC+는 EHC에 비해 소량의 추가적인 지역 탐색을 필요로 하지만 목표 상태까지 전체 탐색 양을 줄일 수 있고 더 짧은 계획을 얻을 수있다. 또한 본 본문에서는 대규모 상태 공간 탐색에 필수적인 효과적인 휴리스틱 추출 방법을 제안한다. 본 논문에서 제안하는 휴리스틱 추출방법은 Graphplan에서 계획 생성을 위해 처음 제안된 계획 그래프를 이용한다. 본 논문에서는 이러한 계획 그래프 기반의 다양한 휴리스틱들을 소개하고, 이들이 계획 생성에 미치는 효과를 실험을 통해 분석해본다.