• Title/Summary/Keyword: Heuristic search

검색결과 536건 처리시간 0.025초

휴리스틱 유전 알고리즘 경로 탐색에 광선 추적 알고리즘을 활용한 경로 최적화 연구 (Path Optimize Research used Ray-Tracing Algorithm in Heuristic-based Genetic Algorithm Pathfinding)

  • 고정운;이동엽
    • 한국게임학회 논문지
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    • 제19권6호
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    • pp.83-90
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    • 2019
  • 휴리스틱 기반의 유전 알고리즘 경로 탐색(H-GAP)은 노드, 에지 정보를 필요로 하지 않기 때문에 기존 경로 탐색 알고리즘의 단점을 보완하고 빠른 속도로 경로 탐색을 수행할 수 있다. 하지만 H-GAP를 이용해 탐색한 경로는 비 노드 기반이기 때문에 불필요한 경로 정보가 포함되어 탐색된 경로가 최적의 경로가 아닐 때도 있다. 본 논문에서는 H-GAP를 이용해 탐색한 경로를 최적화하는 알고리즘을 제안한다. 제안하는 알고리즘은 H-GAP의 경로 탐색이 완료된 후 광선 추적 알고리즘을 이용해 불필요한 경로 정보를 제거하여 경로를 최적화한다.

Optimization of the Travelling Salesman Problem Using a New Hybrid Genetic Algorithm

  • Zakir Hussain Ahmed;Furat Fahad Altukhaim;Abdul Khader Jilani Saudagar;Shakir Khan
    • International Journal of Computer Science & Network Security
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    • 제24권3호
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    • pp.12-22
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    • 2024
  • The travelling salesman problem is very famous and very difficult combinatorial optimization problem that has several applications in operations research, computer science and industrial engineering. As the problem is difficult, finding its optimal solution is computationally very difficult. Thus, several researchers have developed heuristic/metaheuristic algorithms for finding heuristic solutions to the problem instances. In this present study, a new hybrid genetic algorithm (HGA) is suggested to find heuristic solution to the problem. In our HGA we used comprehensive sequential constructive crossover, adaptive mutation, 2-opt search and a new local search algorithm along with a replacement method, then executed our HGA on some standard TSPLIB problem instances, and finally, we compared our HGA with simple genetic algorithm and an existing state-of-the-art method. The experimental studies show the effectiveness of our proposed HGA for the problem.

Harmony Search 알고리즘을 이용한 입체트러스의 단면최적화 (Size Optimization of Space Trusses Based on the Harmony Search Heuristic Algorithm)

  • 이강석;김정희;최창식;이리형
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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    • pp.359-366
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    • 2005
  • Most engineering optimization are based on numerical linear and nonlinear programming methods that require substantial gradient information and usually seek to improve the solution in the neighborhood of a starting point. These algorithm, however, reveal a limited approach to complicated real-world optimization problems. If there is more than one local optimum in the problem, the result may depend on the selection of an initial point, and the obtained optimal solution may not necessarily be the global optimum. This paper describes a new harmony search(HS) meta-heuristic algorithm-based approach for structural size optimization problems with continuous design variables. This recently developed HS algorithm is 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. Two classical space truss optimization problems are presented to demonstrate the effectiveness and robustness of the HS algorithm. The results indicate that the proposed approach is a powerful search and optimization technique that may yield better solutions to structural engineering problems than those obtained using current algorithms.

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후보순위 기반 타부 서치를 이용한 제약 조건을 갖는 작업 순서결정 문제 풀이 (Solving the Constrained Job Sequencing Problem using Candidate Order based Tabu Search)

  • 정성욱;김준우
    • 한국정보시스템학회지:정보시스템연구
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    • 제25권1호
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    • pp.159-182
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    • 2016
  • Purpose This paper aims to develop a novel tabu search algorithm for solving the sequencing problems with precedence constraints. Due to constraints, the traditional meta heuristic methods can generate infeasible solutions during search procedure, which must be carefully dealt with. On the contrary, the candidate order based tabu search (COTS) is based on a novel neighborhood structure that guarantees the feasibility of solutions, and can dealt with a wide range of sequencing problems in flexible manner. Design/methodology/approach Candidate order scheme is a strategy for constructing a feasible sequence by iteratively appending an item at a time, and it has been successfully applied to genetic algorithm. The primary benefit of the candidate order scheme is that it can effectively deal with the additional constraints of sequencing problems and always generates the feasible solutions. In this paper, the candidate order scheme is used to design the neighborhood structure, tabu list and diversification operation of tabu search. Findings The COTS has been applied to the single machine job sequencing problems, and we can see that COTS can find the good solutions whether additional constraints exist or not. Especially, the experiment results reveal that the COTS is a promising approach for solving the sequencing problems with precedence constraints. In addition, the operations of COTS are intuitive and easy to understand, and it is expected that this paper will provide useful insights into the sequencing problems to the practitioners.

배전선로 보호기기 정정에서의 경험적 탐색 방법 (Heuristic Search in Coordination of Overcurrent Protection of Power Distribution Systems)

  • 이승재;박영문;이정원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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    • pp.191-196
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    • 1990
  • By the nature of distribution system, the coordination process of protection devices depends on various heuristic rules. This paper reviews the practical rules that adopted in coordination, and proposes some heuristic rules improving the coordination process.

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물류 센터 위치 선정 및 대리점 할당 모형에 대한 휴리스틱 해법 (Meta-heuristic Method for the Single Source Capacitated Facility Location Problem)

  • 석상문;이상욱
    • 한국콘텐츠학회논문지
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    • 제10권9호
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    • pp.107-116
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    • 2010
  • 시설물 입지 선정 문제(FLP)는 전통적인 최적화 문제중에 하나이다. FLP에 공급제약과 하나의 고객은 하나의 시설물에서만 제품을 공급받을 수 있다는 제약을 추가하면 단일 시설물 공급제약을 가지는 시설물 위치 설정 문제(SSFLP)가 된다. SSFLP는 NP-hard 문제로 알려져 있으며 진화 알고리즘과 같은 휴리스틱 알고리즘을 사용하여 해결하는 것이 일반적이다. 본 논문에서는 SSFLP를 위한 효율적인 진화 알고리즘을 제안한다. 제안하는 알고리즘은 적응형 링크 조절 진화 알고리즘과 3가지 휴리스틱 해 개선 방법을 조합하여 고안되었다. 제안하는 알고리즘을 벤치마크 문제에 적용하여 다른 알고리즘과 성능을 비교분석해 본 결과, 제안하는 알고리즘은 중간 크기의 문제에서 대부분 최적해를 찾았으며 큰 문제에서도 안정된 결과를 보여주었다.

홀로그래픽 저장장치에 대한 GS 인코딩의 정수계획법 모형 및 휴리스틱 (Integer Programming Model and Heuristic on the Guided Scrambling Encoding for Holographic Data Storage)

  • 박태형;이재진
    • 한국통신학회논문지
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    • 제38A권8호
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    • pp.656-661
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    • 2013
  • 홀로그래픽 저장장치의 Guided Scrambling (GS) 인코딩에서는 소스비트에 제어비트를 추가하여 스크램블링된 코드워드에서 변조 제약식을 만족하는 최적의 코드를 선택한다. 본 연구에서는 GS 인코딩 과정을 선형식으로 수식화하여, 제어비트를 직접 계산하는 0-1 정수계획법 모형을 소개한다. 또한 정수계획법의 계산 복잡도를 줄이기 위해 제어비트를 결정하는 이웃탐색 휴리스틱 알고리즘을 개발한다. 개발된 모형은 다양한 코드 행렬 및 제어비트를 갖는 문제들에 적용하여 성능을 비교하였다.

A Heuristic for Dual Mode Routing with Vehicle and Drone

  • Min, Yun-Hong;Chung, Yerim
    • 한국컴퓨터정보학회논문지
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    • 제21권9호
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    • pp.79-84
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    • 2016
  • In this paper we consider the problem of finding the triplet (S,${\pi}$,f), where $S{\subseteq}V$, ${\pi}$ is a sequence of nodes in S and $f:V{\backslash}S{\rightarrow}S$ for a given complete graph G=(V,E). In particular, there exist two costs, $c^V_{uv}$ and $c^D_{uv}$ for $(u,v){\in}E$, and the cost of triplet (S,${\pi}$,f) is defined as $\sum_{i=1}^{{\mid}S{\mid}}c^V_{{\pi}(i){\pi}(i+1)}+2$ ${\sum_{u{\in}V{\backslash}S}c^D_{uf(u)}$. This problem is motivated by the integrated routing of the vehicle and drone for urban delivery services. Since a well-known NP-complete TSP (Traveling Salesman Problem) is a special case of our problem, we cannot expect to have any polynomial-time algorithm unless P=NP. Furthermore, for practical purposes, we may not rely on time-exhaustive enumeration method such as branch-and-bound and branch-and-cut. This paper suggests the simple heuristic which is motivated by the MST (minimum spanning tree)-based approximation algorithm and neighborhood search heuristic for TSP.

경험적 탐색기법에 근거한 배전계통의 선로 재구성 앨고리즘 (NETWORK RECONFIGURATION ALGORITHM FOR AUTOMATED DISTRIBUTION SYSTEM BASED ON THE BEST-FIRST TREE SEARCH)

  • 정경희;김호용;고윤석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.350-353
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    • 1991
  • This study develops an expert system which solves the problems of the MTr/feeder overloads and the feeder constraints in automated radial distribution systems. Then, the objective is to perform the network reconfiguration by switching the tie and sectionalizing switches which eliminates the system violation, while achieving the load balance of the MTrs/feeders. To reduce the search space, an expert system based on heuristic rules is presented, and implemented in AI language Prolog. This system adopts the best-first tree search technique. The computational results are also prepared to show the performance of the heuristic algorithm developed.

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개선된 Randomizing 알고리즘을 이용한 Job Shop 일정계획에 관한 연구 (A Study on the Job Shop Scheduling Using Improved Randomizing Algorithm)

  • 이화기;김민석;이승우
    • 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.