• 품질경영학회지
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• 제13권1호
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• pp.56-64
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• 1985

This paper presents a general algorithm of multi-item continuous review models to obtain simultaneous solutions for ordering quantities and reorder points for each item in an inventory, while satisfying constraints on average inventory investment and reordering workload. Two models are formulated'in each model the heuristic method is utilized, and the partial back-logging is considered. In the first model, the objective function is the minimization of total inventory variable cost. In the second model, the objective function is the minimization of total time-weighted shortages, and the ordering, holding, and stockout costs in this model are independent each other. A numerical example is also solved to present application of each model.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제19권3호
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• pp.289-303
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• 2015

In this paper, an optimal guidance law with terminal angle constraint considering the seeker's lock-on condition, in which the target is located within the field-of-view (FOV) and detection range limits at the end of the midcourse phase, is proposed. The optimal solution is obtained by solving an optimal control problem minimizing the energy cost function weighted by a power of range-to-go subject to the terminal constraints, which can shape the guidance commands and the missile trajectories adjusting guidance gains of the weighting function. The proposed guidance law can be applied to both of the midcourse and terminal phases by setting the desired relative range and look angle to the final interception conditions. The performance of the proposed guidance law is analyzed through nonlinear simulations for various engagement conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4355-4371
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• 2020

Phase retrieval, recovering a signal from phaseless measurements, is generally considered to be an NP-hard problem. This paper adopts an amplitude-based nonconvex optimization cost function to develop a new stochastic gradient algorithm, named stochastic reweighted phase retrieval (SRPR). SRPR is a stochastic gradient iteration algorithm, which runs in two stages: First, we use a truncated sample stochastic variance reduction algorithm to initialize the objective function. The second stage is the gradient refinement stage, which uses continuous updating of the amplitude-based stochastic weighted gradient algorithm to improve the initial estimate. Because of the stochastic method, each iteration of the two stages of SRPR involves only one equation. Therefore, SRPR is simple, scalable, and fast. Compared with the state-of-the-art phase retrieval algorithm, simulation results show that SRPR has a faster convergence speed and fewer magnitude-only measurements required to reconstruct the signal, under the real- or complex- cases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2339-2355
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• 2021

In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

• 지능정보연구
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• 제9권1호
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• pp.71-89
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• 2003

경영 분류 문제에 대한 많은 연구들은 여러가지 기법들간의 성과 비교에 대한 것이었지만, 각각의 연구들마다 가장 좋은 기법이 어떤 것인가에 대해서는 상이한 결론을 내고 있다. 다수의 분류 기법 중에서 가장 좋은 것을 사용하는 방법에 대한 대안으로,분류 기법을 통합하여 성과를 향상시키는 방법이 있다. 본 연구에서는 개별 분류 기법의 결과를 선형 결합하여 예측력을 높이는 방법을 제시하였다. 최 적 선형 결합 가중치를 계산하기 위해 혼합 정수 계 획 법을 사용하였다. 목적 함수로 사용한 오분류 비용의 최소화에서 오분류 비용은 부도 기업을 모형에서 정상으로 예측한 오류와 정상기업을 모형에서 부도 기업으로 예측한 오류의 합으로 정의하였다. 문제 풀이 과정을 단순화하기 위하여 본 논문에서는 절사점 (cutoff value)을 고정하였고, 경계 함수 (threshold function)를 배제하였다. 정수계획법의 계산을 위해 branch 8, bound 방법을 사용하였다. 선형 결합에 의한 모형의 예측력이 개별 기법에 의해 구축된 모형의 예측력을 상회하였고, 그 차이가 통계적으로도 유의하였다.

• 대한안전경영과학회지
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• 제21권2호
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• pp.15-23
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• 2019

Among service industries of knowledge based economic era, the roles of educational service field are becoming more important and standard of educational service makes a direct effect on economic development and social growth. Therefore, accurate measurement of service quality is the most important assignment and the measurement of the service quality remains difficult assignment. So, this researcher classified quality attributes applying weighted value and found potential satisfaction level(PSL) and potential customer demand improvement index(PCDI) for trainees participating in national manpower business so as to suggest measurement of service quality and easiness of use and then, calculated satisfaction position and opportunity cost by quality factor with Taguchi's loss fraction. And, improvable satisfaction level was measured, opportunity cost by degree of customer dissatisfaction was quantitatively measured, and a model that can indicate with economic factors was suggested. In addition, methodology of measuring quality cost that can be reduced by quality improvement and direction of strategic decision-making for deciding items to be improved preferentially were suggested with qualitative index that can indicate the degree of customers' dissatisfaction by loss.

• Steel and Composite Structures
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• 제36권1호
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• pp.31-45
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• 2020

The purpose of this study is to develop an effective iterative two-stage method (ITSM) for structural damage identification of offshore platform structures. In each iteration, a new damage index, Modal Energy-Based Damage Index (MEBI), is proposed to help effectively locate the potential damage elements in the first stage. Then, in the second stage, the beetle antenna search (BAS) algorithm is used to estimate the damage severity of these elements. Compared with the well-known particle swarm optimization (PSO) algorithm and genetic algorithm (GA), this algorithm has lower computational cost. A modal energy based objective function for the optimization process is proposed. Using numerical and experimental data, the efficiency and accuracy of the ITSM are studied. The effects of measurement noise and spatial incompleteness of mode shape are both considered. All the obtained results show that under these influences, the ITSM can accurately identify the true location and severity of damage. The results also show that the objective function based on modal energy is most suitable for the ITSM compared with that based on flexibility and weighted natural frequency-mode shape.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• 품질경영학회지
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• 제18권2호
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• pp.81-92
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• 1990

This paper considers a scheduling of a set of jobs on single and multiple processors, when all jobs have a common due date and earliness and lateness are penalized at different cost rates. The objective is to determine the optimal value of a common due date and an optimal scheduling to minimize a total penalty function. It is also shown that a schedule having minimum weighted completion time variances must be V-shaped. For identical processors, a polynomial scheduling algorithm with the secondary objectives of minimizing makespan and machine occupancy is developed and a numerical example is presented.

• International Journal of Control, Automation, and Systems
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• 제5권2호
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• pp.212-217
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• 2007

A new method of designing multi-loop PID controllers is presented in this paper. By using the generalized IMC-PID method for multi-loop systems, the optimization problem involved in finding the PID parameters is efficiently simplified to find the optimum closed-loop time constant in a reduced search space. A weighted sum Mp criterion is proposed as a performance cost function to cope with both the performance and robustness of a multi-loop control system. Several illustrative examples are included to demonstrate the improved performance of the multi-loop PID controllers obtained by the proposed design method.