• 제목/요약/키워드: Probabilistic Search

검색결과 98건 처리시간 0.243초

Combinatorial particle swarm optimization for solving blocking flowshop scheduling problem

  • Eddaly, Mansour;Jarboui, Bassem;Siarry, Patrick
    • Journal of Computational Design and Engineering
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    • 제3권4호
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    • pp.295-311
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    • 2016
  • This paper addresses to the flowshop scheduling problem with blocking constraints. The objective is to minimize the makespan criterion. We propose a hybrid combinatorial particle swarm optimization algorithm (HCPSO) as a resolution technique for solving this problem. At the initialization, different priority rules are exploited. Experimental study and statistical analysis were performed to select the most adapted one for this problem. Then, the swarm behavior is tested for solving a combinatorial optimization problem such as a sequencing problem under constraints. Finally, an iterated local search algorithm based on probabilistic perturbation is sequentially introduced to the particle swarm optimization algorithm for improving the quality of solution. The computational results show that our approach is able to improve several best known solutions of the literature. In fact, 76 solutions among 120 were improved. Moreover, HCPSO outperforms the compared methods in terms of quality of solutions in short time requirements. Also, the performance of the proposed approach is evaluated according to a real-world industrial problem.

혼합 유전 알고리즘을 이용한 GDP/MINLP로 표현된 공정 최적화 (Process Optimization Formulated in GDP/MINLP Using Hybrid Genetic Algorithm)

  • 송상옥;장영중;김구회;윤인섭
    • 제어로봇시스템학회논문지
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    • 제9권2호
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    • pp.168-175
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    • 2003
  • A new algorithm based on Genetic Algorithms is proposed f3r solving process optimization problems formulated in MINLP, GDP and hybrid MINLP/GDP. This work is focused especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is experimented and many heuristics are adopted. Real and binary coded Genetic Algorithm initiates the global search in the entire search space and at every stage Simulated Annealing makes the candidates to climb up the local hills. Multi-Niche Crowding method is adopted as the multimodal function optimization technique. and the adaptation of probabilistic parameters and dynamic penalty systems are also implemented. New strategies to take the logical variables and constraints into consideration are proposed, as well. Various test problems selected from many fields of process systems engineering are tried and satisfactory results are obtained.

퍼지집합이론을 이용한 발전기보수유지계획수립 (Maintenance Scheduling of Generation System by Fuzzy Set Theory)

  • 박정제;최재석;백웅기;차준민
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2009년도 제40회 하계학술대회
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    • pp.127_128
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    • 2009
  • A new technique using a search method which is based on fuzzy multi-criteria function is proposed for GMS(generator maintenance scheduling) in order to consider multi-objective function. Not only minimization of probabilistic production cost but also maximization of system reliability level are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.

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퍼지이론을 이용한 유연한 발전기보수유지계획 수립에 관한 연구 (A Study on the Flexible Generator Maintenance Scheduling using Fuzzy Theory)

  • 김홍식;문승필;최재석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 C
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    • pp.1104-1107
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    • 1999
  • A new technique using search method based on fuzzy multi-criteria function is proposed fur flexible generator maintenance scheduling. Minimization of probabilistic production cost, maximization of system reliability level and air pollution are considered fur fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by the simulation results of the real size model system of KEPCO-1997 SYSTEM.

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토너먼트 경쟁에 의한 경쟁 공진화 알고리듬 (A Competitive Coevolutionary Algorithm with Tournament Competitions)

  • 김선진;김여근;김재윤;곽재승
    • 대한산업공학회지
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    • 제26권2호
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    • pp.101-109
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    • 2000
  • A competitive coevolutionary algorithm is a probabilistic search method that imitates the biological process that two or more species competitively coevolve through evolutionary arms race. The algorithm has been used to efficiently solve adversarial problems that can be formulated as the search for a solution that is correct over a large space of test cases. We develop an efficient competitive coevolutionary algorithm to solve adversarial problems with high complexity. The algorithm developed in this paper employs three methods: tournament competitions, exchanging of entry fee, and localized coevolution. Analyzed in this paper are the effects of the methods on the performance of the proposed algorithm. The extensive experiments show that our algorithm can progress an evolutionary arms race between competitive coevolving species and then outperforms existing approaches to solving the adversarial problems.

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클라이언트 서버 환경에서 한글텍스트 검색을 위한 베스티매치 알고리즘의 구현 (An Implementation of Best Match Algorithm for Korean Text Retrieval in the Client/Server Environment)

    • 한국도서관정보학회지
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    • 제32권1호
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    • pp.249-260
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    • 2001
  • This paper presents the application of best match search algorithm in the client/server system for natural language access to Web-based database. For this purpose, the procedures to process Korean word variants as well as to execute probabilistic weighting scheme have been implemented in the client/server system. The experimental runs have been done using a Korean test set which included documents, queries and relevance judgements. The experimental results demonstrate that best match retrieval with relevance information is better than the retrieval without it.

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진화 연산을 이용한 능동외곽기반의 윤곽선검출에 관한 연구 (Active Contour Based Edge Detection Using Evolutionary Computation)

  • 강현태;조덕환;황기현;문경준;박준호;이화석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 D
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    • pp.2405-2407
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    • 2001
  • In this paper, we apply and evolutionary computation(EC), probabilistic optimization algorithm, to active contour. A number of problems exist associated with such as algorithm initialization, existence of local minima, non-convex search space, and the selection of model parameters in conventional models. We propose an adequate fitness function for these problems. The determination of fitness function adequate to active contour using EC is important in search capability. As a result of applying the proposed method to non-convex object shape, we improve the unstability and contraction phenomena, in nature, of snake generated in deformable contour optimization.

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분산 객체의 확률적 비례 검색 기반 전송률 향상 검색 알고리즘 (Search Algorithm for Advanced Transmission Rate based on Probabilistic Proportion Search of Distributed Objects)

  • 김분희
    • 한국컴퓨터정보학회논문지
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    • 제11권3호
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    • pp.49-56
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    • 2006
  • P2P 분산 시스템의 가장 큰 특징은 해당 피어들이 항상 온라인 상태일 것이라는 보장이 없다는 것이다. 즉 P2P 시스템을 이용할 때에는 해당 피어로부터 파일을 다운로드받다가 다운로드 되지 않는 경우가 발생하게 된다. 이를 해결하기 위한 연구의 대부분은 재전송이라는 방법에 의존하고 있다. 이는 P2P 시스템의 성능 저하의 원인이 되므로 이에 대한 해결책이 필요하다. 본 연구에서는 해당 P2P 시스템을 이용하는 사용자의 평균 이용 시간대의 분석 자료를 자원 제공자 선택의 기준으로 적용하여 자원 전송 보장성을 높이고, 또한 인기도 높은 자원에 대해서 자료 전송 기회를 높여주는 역할의 기존의 분산 객체 리플리케이션 기법들과의 조합에 의한 분산 객체 전송률이 향상된 검색 알고리즘을 제안한다.

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DL-RRT* algorithm for least dose path Re-planning in dynamic radioactive environments

  • Chao, Nan;Liu, Yong-kuo;Xia, Hong;Peng, Min-jun;Ayodeji, Abiodun
    • Nuclear Engineering and Technology
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    • 제51권3호
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    • pp.825-836
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    • 2019
  • One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

위상배열 레이다 검출 및 추적 매개변수의 최적 스케쥴링 (Optimal Scheduling of Detection and Tracking Parameters in Phased Array Radars)

  • 정영헌;김현수;홍순목
    • 전자공학회논문지S
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    • 제36S권7호
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    • pp.50-61
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    • 1999
  • 이 논문에서는 클러터 환경에서 항적 유지에 필요한 레이다 에너지를 최소하하기 위한 위상배열 레이디의 표적 검출 및 추적 매개변수 제어방법을 제시한다. 이를 위해 위상배열 레이다의 표적 탐색과정에서 비롯되는 표적 검출과정을 수학적 모델로 전개한다. 수학적 전개과정을 통해 표적 검출과정에서 발생하는 클리터나 측정 잡음에 의한 거짓 정보(false alarm)등과 같은 실제 표적이외의 측정을 고려한다. 추적필터 역시 클리터의 영향을 고려하기 위해 확률적 데이터 연관(Probabilistic Data Association: PDA)필터의 수정된 리카티 방정식의 근사식을 이용한다. 표적 탐색과정과 추적모델을 바탕으로, 최적의 매개변수 계획(scheduling)문제를 비선형 최적제어문제로 수식화하며, 최적제어문제의 해를 얻기 위해 제한조건을 가진 비선형 최적화 문제를 푼다.

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