• 제목/요약/키워드: Search algorithms

검색결과 1,328건 처리시간 0.028초

Dolphin Echolocation Optimization: Continuous search space

  • Kaveh, A.;Farhoudi, N.
    • Advances in Computational Design
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    • 제1권2호
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    • pp.175-194
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    • 2016
  • Nature has provided inspiration for most of the man-made technologies. Scientists believe that dolphins are the second to humans in smartness and intelligence. Echolocation is the biological sonar used by dolphins for navigation and hunting in various environments. This ability of dolphins is mimicked in this paper to develop a new optimization method. Dolphin Echolocation Optimization (DEO) is an optimization method based on dolphin's approach for hunting food and exploration of environment. DEO has already been developed for discrete optimization search space and here it is extended to continuous search space. DEO has simple rules and is adjustable for predetermined computational cost. DEO provides the optimum results and leads to alternative optimality curves suitable for the problem. This algorithm has a few parameters and it is applicable to a wide range of problems like other metaheuristic algorithms. In the present work, the efficiency of this approach is demonstrated using standard benchmark problems.

직접탐색법을 이용한 RC 프레임 구조물의 설계 최적화 (Design Optimization for RC Frame Structures Using Direct Search Method)

  • 곽효경;김지은
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2007년도 정기 학술대회 논문집
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    • pp.583-588
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    • 2007
  • For the purpose of optimum design of RC frame structures. pre-determined section database of column and beam are constructed and arranged in order of the resisting capacity. Then, regression equations representing the relation between section number and resisting capacity are derived. In advance. effective optimization algorithms which search optimized solution quickly using direct search method from these database are proposed. Moreover. the investigation for the applicability and effectiveness of the introduced design procedure is conducted through correlation study for example structures.

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IP 주소 검색을 위한 Priority Trie (An Efficient IP address Lookup Algorithm Using a Priority-Trie)

  • 임혜숙;문주형
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2006년도 하계종합학술대회
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    • pp.3-4
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    • 2006
  • Fast IP address lookup in routers is essential to achieve packet forwarding in wire-speed. The longest prefix matching for IP address lookup is more complex than exact matching because of its dual dimensions, length and value. By thoroughly studying the current proposals for IP address lookup, we find out that the binary search could be a low-cost solution while providing high performance. Most of the existing binary search algorithms based on trie have simple data structures which can be easily implemented, but they have some problems because of empty internal nodes. The proposed algorithm is based on trie structure, but empty internal nodes are replaced by priority prefixes. The best-matching-prefix search in the proposed algorithm is more efficiently performed since search can be finished earlier when input is matched with a priority prefix. The performance evaluation results show that the constructed priority-trie has very good performance in the lookup speed and the scalability.

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Multi-Exchange Neighborhood Search Heuristics for the Multi-Source Capacitated Facility Location Problem

  • Chyu, Chiuh-Cheng;Chang, Wei-Shung
    • Industrial Engineering and Management Systems
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    • 제8권1호
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    • pp.29-36
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    • 2009
  • We present two local-search based metaheuristics for the multi-source capacitated facility location problem. In such a problem, each customer's demand can be supplied by one or more facilities. The problem is NP-hard and the number of locations in the optimal solution is unknown. To keep the search process effective, the proposed methods adopt the following features: (1) a multi-exchange neighborhood structure, (2) a tabu list that keeps track of recently visited solutions, and (3) a multi-start to enhance the diversified search paths. The transportation simplex method is applied in an efficient manner to obtain the optimal solutions to neighbors of the current solution under the algorithm framework. Two in-and-out selection rules are also proposed in the algorithms with the purpose of finding promising solutions in a short computational time. Our computational results for some of the benchmark instances, as well as some instances generated using a method in the literature, have demonstrated the effectiveness of this approach.

유성생식 유전알고리즘 : 다중선택과 이배성이 탐색성능에 미치는 영향 (Sexual Reproduction Genetic Algorithms: The Effects of Multi-Selection & Diploidy on Search Performances)

  • 류근배;최영준;김창업;이학성;정창기
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.1006-1010
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    • 1995
  • This paper describes Sexual Reproduction Genetic Algorithm(SRGA) for function optimization. In SRGA, each individual utilize a diploid chromosome structure. Sex cells(gametes) are produced through artificial meiosis in which crossover and mutation occur. The proposed method has two selection operators, one, individual selection which selects the individual to fertilize, and the other, gamete selection which makes zygote for offspring production. We consider the effects of multi-selection and diploidy on search performance. SRGA improves local and global search(exploitation and exploration) and show optimum tracking performance in nonstationary environments. Gray coding is incorporated to transforming the search space and Genic uniform distribution method is proposed to alleviate the problem of premature convergence.

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A Built-In Redundancy Analysis with a Minimized Binary Search Tree

  • Cho, Hyung-Jun;Kang, Woo-Heon;Kang, Sung-Ho
    • ETRI Journal
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    • 제32권4호
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    • pp.638-641
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    • 2010
  • With the growth of memory capacity and density, memory testing and repair with the goal of yield improvement have become more important. Therefore, the development of high efficiency redundancy analysis algorithms is essential to improve yield rate. In this letter, we propose an improved built-in redundancy analysis (BIRA) algorithm with a minimized binary search tree made by simple calculations. The tree is constructed until finding a solution from the most probable branch. This greatly reduces the search spaces for a solution. The proposed BIRA algorithm results in 100% repair efficiency and fast redundancy analysis.

Symbiotic Organisms Search for Constrained Optimization Problems

  • Wang, Yanjiao;Tao, Huanhuan;Ma, Zhuang
    • Journal of Information Processing Systems
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    • 제16권1호
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    • pp.210-223
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    • 2020
  • Since constrained optimization algorithms are easy to fall into local optimum and their ability of searching are weak, an improved symbiotic organisms search algorithm with mixed strategy based on adaptive ε constrained (ε_SOSMS) is proposed in this paper. Firstly, an adaptive ε constrained method is presented to balance the relationship between the constrained violation degrees and fitness. Secondly, the evolutionary strategies of symbiotic organisms search algorithm are improved as follows. Selecting different best individuals according to the proportion of feasible individuals and infeasible individuals to make evolutionary strategy more suitable for solving constrained optimization problems, and the individual comparison criteria is replaced with population selection strategy, which can better enhance the diversity of population. Finally, numerical experiments on 13 benchmark functions show that not only is ε_SOSMS able to converge to the global optimal solution, but also it has better robustness.

Sinusoidal Map Jumping Gravity Search Algorithm Based on Asynchronous Learning

  • Zhou, Xinxin;Zhu, Guangwei
    • Journal of Information Processing Systems
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    • 제18권3호
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    • pp.332-343
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    • 2022
  • To address the problems of the gravitational search algorithm (GSA) in which the population is prone to converge prematurely and fall into the local solution when solving the single-objective optimization problem, a sine map jumping gravity search algorithm based on asynchronous learning is proposed. First, a learning mechanism is introduced into the GSA. The agents keep learning from the excellent agents of the population while they are evolving, thus maintaining the memory and sharing of evolution information, addressing the algorithm's shortcoming in evolution that particle information depends on the current position information only, improving the diversity of the population, and avoiding premature convergence. Second, the sine function is used to map the change of the particle velocity into the position probability to improve the convergence accuracy. Third, the Levy flight strategy is introduced to prevent particles from falling into the local optimization. Finally, the proposed algorithm and other intelligent algorithms are simulated on 18 benchmark functions. The simulation results show that the proposed algorithm achieved improved the better performance.

시드 정제 기술을 이용한 웹 스팸 필터링의 품질 향상 (Improving the Quality of Web Spam Filtering by Using Seed Refinement)

  • 무하마드 아티프 쿠레시;윤태섭;이정훈;황규영
    • 전자공학회논문지CI
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    • 제48권6호
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    • pp.123-139
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    • 2011
  • 웹 스팸은 중요하지 않은 웹 페이지들의 중요도를 승격시키기 때문에 웹 검색 결과의 품질에 중대한 영향을 준다. 따라서 웹 검색 엔진은 웹 스팸을 제거할 필요가 있다. 웹 스팸 필터링은 스팸 페이지들, 즉 웹 스팸에 기여하는 웹 페이지들을 식별하는 것이며, 잘 알려진 웹 스팸 필터링 알고리즘으로는 Trust Rank, Anti-Trust Rank, Spam Mass, 그리고 Link Farm Spam이 있다. 이러한 알고리즘들의 결과 품질은 입력 시드(input seed)에 따라 달라진다. 따라서 입력 시드를 정제(refinement) 함으로써, 웹 스팸 필터링의 품질을 향상 시킬 수 있다. 본 논문에서는 잘 알려진 네 가지 알고리즘에 대한 시드를 정제하는 기술을 제안한다. 다음으로, 이러한 기술을 원(original) 알고리즘에 각각 적용하는 방법으로 알고리즘을 수정한다. 이를 수정된 웹 스팸 필터링 알고리즘이라고 부른다. 본 논문에서는 또한, 웹 스팸 필터링을 좀 더 향상시키기 위한 전략을 제안한다. 이 전략에서는 수정된 알고리즘들을 수행 순서상의 적절한 위치에 배치함으로써 알고리즘들의 상호간 지원을 통해 전체적으로 성능을 향상시키는 가능성을 고려한다. 마지막으로, 실험에서는 시드 정제의 효과를 보인다. 이를 위해, 먼저, 수정된 알고리즘의 웹 스팸 필터링 품질이 원 알고리즘의 품질보다 더 우수함을 보인다. 다음으로, 웹 스팸 필터링 알고리즘들이 수행되는 순서의 조합 중 가장 성능이 우수한 조합이 가장 뛰어난 잘 알려진 알고리즘과 비교하여 정확도(precision)를 유지하면서 파라미터의 전형적인 값 범위 내에서 재현율(recall)은 최대 1.38배까지 높게 향상됨을 보인다.

강화된 유전알고리즘을 이용한 이중 동조 기반 퍼지 예측시스템 설계 및 응용 (Design of Fuzzy Prediction System based on Dual Tuning using Enhanced Genetic Algorithms)

  • 방영근;이철희
    • 전기학회논문지
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    • 제59권1호
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    • pp.184-191
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    • 2010
  • Many researchers have been considering genetic algorithms to system optimization problems. Especially, real-coded genetic algorithms are very effective techniques because they are simpler in coding procedures than binary-coded genetic algorithms and can reduce extra works that increase the length of chromosome for wide search space. Thus, this paper presents a fuzzy system design technique to improve the performance of the fuzzy system. The proposed system consists of two procedures. The primary tuning procedure coarsely tunes fuzzy sets of the system using the k-means clustering algorithm of which the structure is very simple, and then the secondary tuning procedure finely tunes the fuzzy sets using enhanced real-coded genetic algorithms based on the primary procedure. In addition, this paper constructs multiple fuzzy systems using a data preprocessing procedure which is contrived for reflecting various characteristics of nonlinear data. Finally, the proposed fuzzy system is applied to the field of time series prediction and the effectiveness of the proposed techniques are verified by simulations of typical time series examples.