• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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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.

• Journal of information and communication convergence engineering
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• v.20 no.2
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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.

• Journal of Korea Game Society
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• v.17 no.5
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• pp.123-132
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• 2017

The path-finding algorithm refers to an algorithm for navigating the route order from the current position to the destination in a virtual world in a game. The conventional path-finding algorithm performs graph search based on cost such as A-Star and Dijkstra. A-Star and Dijkstra require movable node and edge data in the world map, so it is difficult to apply online games with lots of map data. In this paper, we provide a Heuristic-based Genetic Algorithm Path-finding(HGAP) using Genetic Algorithm(GA). Genetic Algorithm is a path-finding algorithm applicable to game with variable environment and lots of map data. It seek solutions through mating, crossing, mutation and evolutionary operations without the map data. The proposed algorithm is based on Binary-Coded Genetic Algorithm and searches for a path by performing a heuristic operation that estimates a path to a destination to arrive at a destination more quickly.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.611-617
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• 2000

Asynchronous mode W-CDMA system is kmown to be quite appropriate to the next generation mobile communication system, especially in a non-homogenious cellular architecture. In this case, however, each base station needs to use different spreading code for identification, so it is a demeanding task for a mobile terminal to find the best cell site and get an accurate code synchronization at the beginning of a communication. Since slow acquisition of a base station could mean the failure of initiation, a fast algorithm to accelerate the cell search process is essential. In this paper, a new cell search algorithm based on the binary code position modulation within the code block is proposed. Different cell sites are identified by different hopping code sequences, andeach position modulation is performed by the hopping code. The proposed algorithm is proved to make the cell search time in most places in a cell much shorter than the previous algorithms, and to make the receiver implementation simpler.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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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 ...

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.193-193
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• 2004

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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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.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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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.