• 제목/요약/키워드: Binary search algorithm

검색결과 154건 처리시간 0.025초

다수 표면실장기계를 포함하는 PCB 조립라인의 라인균형화 알고리즘 설계 (Design of a line balancing algorithm for the PCB assembly line including multiple surface mounters)

  • 김진철;이성한;김대원;이범희
    • 제어로봇시스템학회논문지
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    • 제3권4호
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    • pp.381-388
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    • 1997
  • This paper proposes a heuristic algorithm to efficiently perform line balancing in the PCB assembly line including multiple surface mounters efficiently. Generally, the problems in line balancing are classified into two kinds. Firstly, is the determining of the minimum number of machines required for achieving the desired production rate. Secondly, is the assign of jobs to multiple machines in order to minimize the cycle time which is defined as a maximum among the working times of machines when the number of machines is fixed. In this paper, we deal with the latter. We consider a PCB assembly line, including the multiple surface mounters arranged serially as a target system. Also, the conveyor is assumed to move at a constant speed and have no buffer. Considering that the minimum number of machines required for the desired production rate is a discrete nonincreasing function which is inversely proportional to the cycle time, we propose an optimization algorithm for line balancing by using the binary search method. The algorithm is validated through computer simulation, the results of which show that their shapes coincide nearly with those of optimal line balancing efficiency graphs regardless of the number of components, the performance of surface mounters, and the structure of assembly line.

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Dual-Encoded Features from Both Spatial and Curvelet Domains for Image Smoke Recognition

  • Yuan, Feiniu;Tang, Tiantian;Xia, Xue;Shi, Jinting;Li, Shuying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권4호
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    • pp.2078-2093
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    • 2019
  • Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

High Utility Itemset Mining by Using Binary PSO Algorithm with V-shaped Transfer Function and Nonlinear Acceleration Coefficient Strategy

  • Tao, Bodong;Shin, Ok Keun;Park, Hyu Chan
    • Journal of information and communication convergence engineering
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    • 제20권2호
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    • pp.103-112
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    • 2022
  • The goal of pattern mining is to identify novel patterns in a database. High utility itemset mining (HUIM) is a research direction for pattern mining. This is different from frequent itemset mining (FIM), which additionally considers the quantity and profit of the commodity. Several algorithms have been used to mine high utility itemsets (HUIs). The original BPSO algorithm lacks local search capabilities in the subsequent stage, resulting in insufficient HUIs to be mined. Compared to the transfer function used in the original PSO algorithm, the V-shaped transfer function more sufficiently reflects the probability between the velocity and position change of the particles. Considering the influence of the acceleration factor on the particle motion mode and trajectory, a nonlinear acceleration strategy was used to enhance the search ability of the particles. Experiments show that the number of mined HUIs is 73% higher than that of the original BPSO algorithm, which indicates better performance of the proposed algorithm.

휴리스틱 기반의 유전 알고리즘을 활용한 경로 탐색 알고리즘 (Path-finding Algorithm using Heuristic-based Genetic Algorithm)

  • 고정운;이동엽
    • 한국게임학회 논문지
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    • 제17권5호
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    • pp.123-132
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    • 2017
  • 경로 탐색 알고리즘은 이동 가능한 에이전트가 게임 내의 가상 월드에서 현재 위치로부터 목적지까지 가는 경로를 탐색하는 알고리즘을 뜻한다. 기존의 경로 탐색 알고리즘은 A*, Dijkstra와 같이 비용기반으로 그래프 탐색을 수행한다. A*와 Dijkstra는 월드 맵에서 이동 가능한 노드와 에지 정보들을 필요로 해서 맵의 정보가 다양하고 많은 온라인 게임에 적용하기 힘들다. 본 논문에서는 가변환경이나 맵의 데이터가 방대한 게임에서 적용 가능한 경로 탐색 알고리즘을 개발하기 위해 맵의 정보 없이 교배, 교차, 돌연변이, 진화 연산을 통해 해를 찾는 유전 알고리즘(Genetic Algorithm, GA)을 활용한 Heuristic-based Genetic Algorithm Path-finding(HGAP)를 제안한다. 제안하는 알고리즘은 Binary-Coded Genetic Algorithm을 기반으로 하며 목적지에 더 빨리 도달하기 위해 목적지로 가는 경로를 추정하는 휴리스틱 연산을 수행하여 경로를 탐색한다.

유전 알고리듬을 이용한 무인운반차시스템의 운반경로 결정 (Determination of Guide Path of AGVs Using Genetic Algorithm)

  • 장석화
    • 산업경영시스템학회지
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    • 제26권4호
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    • pp.23-30
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    • 2003
  • This study develops an efficient heuristic which is based on genetic approach for AGVs flow path layout problem. The suggested solution approach uses a algorithm to replace two 0-1 integer programming models and a branch-and-bound search algorithm. Genetic algorithms are a class of heuristic and optimization techniques that imitate the natural selection and evolutionary process. The solution is to determine the flow direction of line in network AGVs. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. Genetic algorithm procedure is suggested, and a simple illustrative example is shown to explain the procedure.

비동기 W-CDMA 시스템을 위한 코드블럭 내의 코드위치변조를 이용한 고속 셀 탐색 알고리즘 (A Fast Cell Search Algorithm using Code Position Modulation within code block in Asynchronous W-CDMA System)

  • 최정현;김낙명
    • 한국통신학회논문지
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    • 제25권5A호
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    • pp.611-617
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    • 2000
  • 비동기 방식 W-CDMA 시스템은 동기식 방식보다 복합적인 셀 구조를 갖는 차세대 이동통신 시스템에 적합하다는 장점이 있다. 그러나, 이 경우 각 기지국마다 서로 다른 코드를 부여하기 때문에 단말기가 통화가능한 셀을 찾고 코드 동기를 이루는 데에 오랜 시간이 걸린다. 셀 획득의 지연은 통화 실패로 이어질 수 있으므로, 비동기 방식 W-CDMA 시스템을 구현하기 위해서는 고속 셀 탐색 알고리즘이 필수적인 기술이다. 본 논문에서는 도약 코드 시퀀스에 의하여 셀을 구분하고, 코드 블록 내의 이진코드이 위치를 도약코드를 사용하여 변화시킴으로써 기지국의 셀을 찾아내는 코드블럭 내의 코드 위치변조를 이용한 고속 셀 탐색 알고리즘을 제안한다. 제안된 방식은 기존의 방식에 비하여 보다 빠른 시간내에 셀을 찾을 수 있으며, 수신기도 더 간단하게 구현될 수 있다는 장점이 있다.

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Nonlinear System Modelling Using Neural Network and Genetic Algorithm

  • Kim, Hong-Bok;Kim, Jung-Keun;Hwang, Seung-Wook;Ha, Yun-Su;Jin, Gang-Gyoo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.71.2-71
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    • 2001
  • This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...

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Experimental Study on Modifiable Walking Pattern Generation for Handling Infeasible Navigational Commands

  • Hong, Young-Dae;Lee, Bumjoo
    • Journal of Electrical Engineering and Technology
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    • 제10권6호
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    • pp.2368-2375
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    • 2015
  • To accommodate various navigational commands, a humanoid should be able to change its walking motion in real time. Using the modifiable walking pattern generation (MWPG) algorithm, a humanoid can handle dynamic walking commands by changing its walking period, step length, and direction independently. If the humanoid is given a command to perform an infeasible movement, the algorithm substitutes the infeasible command with a feasible one using binary search. The feasible navigational command is subsequently translated into the desired center-of-mass (CM) state. Every sample time CM reference is generated using a zero-moment-point (ZMP) variation scheme. Based on this algorithm, various complex walking patterns can be generated, including backward and sideways walking, without detailed consideration of the feasibility of the navigational commands. In a previous study, the effectiveness of the MWPG algorithm was verified by dynamic simulation. This paper presents experimental results obtained using the small-sized humanoid robot platform DARwIn-OP.

A Boolean Equivalence Testing Algorithm based on a Derivational Method

  • Moon, Gyo-Sik
    • Journal of Electrical Engineering and information Science
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    • 제2권5호
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    • pp.1-8
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    • 1997
  • The main purpose of the Boolean equivalence problem is to verify that two Boolean expressions have the same functionality. Simulation has been extensively used as the standard method for the equivalence problem. Obviously, the number of tests required to perform a satisfactory coverage grows exponentially with the number of input variables. However, formal methods as opposed to simulation are getting more attention from the community. We propose a new algorithm called the Cover-Merge Algorithm based on a derivational method using the concept of cover and merge for the equivalence problem and investigate its theoretical aspects. Because of the difficulty of the problem, we emphasize simplification techniques in order to reduce the search space or problem size. Heuristics based on types of merges are developed to speed up the derivation process by allowing simplifications. In comparison with widely used technique called Binary Decision Diagram or BDD, the algorithm proposed outperforms BDD in nearly all cases of input including standard benchmark problems.

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