• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.13-16
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• 2004

This paper deals with a one-searcher multi-target search problem where targets with different detection priorities move in Markov processes in each discrete time over a given space search area, and the total number of search time intervals is fixed. A limited search resource is available in each search time interval and an exponential detection function is assumed. The searcher can obtain a target detection award, if detected, which represents the detection priority of target and is non-increasing with time. The objective is to establish the optimal search plan which allocates the search resource effort over the search areas in each time interval in order to maximize the total detection award. In the analysis, the given problem is decomposed into intervalwise individual search problems each being treated as a single stationary target problem for each time interval. An associated iterative procedure is derived to solve a sequence of stationary target problems. The computational results show that the proposed algorithm guarantees optimality.

• Convergence Security Journal
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• v.10 no.1
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• pp.55-61
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• 2010

It is of great practical interest to deciding when to stop testing a software system in development phase and transfer it to the user. This decision problem called an optimal release policies. In this paper, because of the possibility of introducing new faults when correcting or modifying the software, we were researched release comparative policies which based on infinite failure NHPP model and types of interval failure times. The policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement can optimal software release times. In a numerical example, applied data which were patterns, if intensity function constant or increasing, decreasing, estimated software optimal release time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.1-8
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• 2003

The operation and management of a plant require proper accounting for the constraints coming from reliability requirements as well as from budget and resource considerations. Most of the mathematical methods to decide the inspection time interval for plant maintenance by reliability theory are too complicated to be solved. Moreover, the mathematical and theoretical models are not usually cases in the practical applications. In order to overcome these problems, we propose a new the decision-making method of optimal inspection interval to minimize the maintenance cost by reliability theory and genetic algorithm (GA). The most merit of the proposed method is to decide the inspection interval for a plant machine of which failure rate $\lambda$(t) conforms to any probability distribution. Therefore, this method is more practical. The efficiency of the proposed method is verified by comparing the results obtained by GA-based method with the inspection model haying regular time interval.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.47-57
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• 1992

The purpose of this paper is to improve the operation performance of unit-load Automated Guided Vehicles (AGV's) used as a carrier and mobile workstation in a flow-shop type flexible manufacturing system. An algorithm is developed to determine the optimal job sequence which minimizes the vehicle idle time on the line and the production makespan by the use of the entering interval and travel time between workcenters. An entering times of AGV's and the minimum number of AGV's required are calculated by optimal job sequence. When the numbe rof AGV's is limited, enterling times of AGV's are adjusted to maximize the efficient use of vehicles. A numerical example is given to illustrate the application of the algorithm.

• Journal of Biosystems Engineering
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• v.23 no.3
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• pp.211-218
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• 1998

A variable flow-controlled boom sprayer was developed and evaluated. Field tests were conducted to evaluate the adoptability of the sprayerr with optimal conditions. Negative response time was obtained from the field test because pump and PTO were interlocked with the speed of sprayer. Another reason for the negative value was due to the definition of the response time. With constant on-time control, the system was unstable at the conditions of small tolerance and long control interval. The performances of the spray system were stable and accurate. The stable and synchronous responses were achieved with a variable on-time control. The flow control system with an optimal condition (1.0 sec of control interval, 2 of damping ratio, 1% of tolerance) provided the proper performance for uniform spraying. A standard operating procedure of the flow compensating boom sprayer for the ground speed variation was presented and recommended.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.55-76
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• 2000

We propose a general solution methodology for identifying the optimal aggregation interval sizes as a function of the traffic dynamics and frequency of observations for four cases : i) link travel time estimation, ii) corridor/route travel time estimation, iii) link travel time forecasting. and iv) corridor/route travel time forecasting. We first develop statistical models which define Mean Square Error (MSE) for four different cases and interpret the models from a traffic flow perspective. The emphasis is on i) the tradeoff between the Precision and bias, 2) the difference between estimation and forecasting, and 3) the implication of the correlation between links on the corridor/route travel time estimation and forecasting, We then demonstrate the Proposed models to the real-world travel time data from Houston, Texas which were collected as Part of the Automatic Vehicle Identification (AVI) system of the Houston Transtar system. The best aggregation interval sizes for the link travel time estimation and forecasting were different and the function of the traffic dynamics. For the best aggregation interval sizes for the corridor/route travel time estimation and forecasting, the covariance between links had an important effect.

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.440-445
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• 1999

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.388-388
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• 2000

The complexity of nonlinear systems makes it difficult to ascertain their behavior using classical methods of analysis. Many efforts have been focused on the advanced algorithms and techniques that hold the promise of improving real-time optimal control while at the same time providing higher accuracy. In this paper, a fuzzy cell mapping method of real-time optimal control far nonlinear dynamical systems is proposed. This approach combines fuzzy logic with cell mapping techniques in order to find the optimal input level and optimal time interval in the finite set which change the state of a system to achieve a desired obiective. In order to illustrate this method, we analyze the behavior of an inverted pendulum using fuzzy cell mapping.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.1
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• pp.170-176
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• 2001

An optimization problem to obtain the optimal replacement interval considering the salvage values is studied. The system is minimally repaired at failure and is replaced by new one at age T(periodic replacement policy with minimal repair of Barlow and Hunter〔2〕). Our model assumes that the time horizon associated with the number of replacements is random The total expected cost considering the salvage values with random time horizon is obtained and the optimal replacement interval minimizing the cost is found by numerical methods. Comparisons between non-considered salvage values and this case are made by a numerical example.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.91-98
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• 2017

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require higher computational cost and larger processing time. Therefore it is necessary to design efficient algorithm that classifies PVC(premature ventricular contraction) and decreases computational cost by accurately detecting minimal feature point based on only R peak through optimal R wave. We propose an optimal R wave detection and PVC classification method through extracting minimal feature point in IoT environment. For this purpose, we detected R wave through optimal threshold value and extracted RR interval and R peak pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through RR interval and R peak pattern. The performance of R wave detection and PVC classification is evaluated by using record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.758% in R wave detection and the rate of 93.94% in PVC classification.