• 산업공학
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• 제24권4호
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• pp.396-407
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• 2011

We develop a cash management model in which firms face randomly occurred investment projects and retrieve investments upon the maturity of these projects. Using the Markov Decision Problem approach, we examine a control policy which dynamically adjusts the cash balance under the discounted cost criterion. The existence of an optimal policy is shown under some conditions. The optimal solution procedure is developed to find the optimal points and the optimal sizes for adjusting the cash balance. In numerical experiment, we investigate important structural properties of the optimal cash management policy.

• 산업기술연구
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• 제21권B호
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• pp.85-89
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• 2001

In this paper, we analyze a time-based update method in location management and calculate the optimal time-interval. The probability that an MT is j rings away from the center cell is obtained by computer programming. And using these values, an exact analysis is made for the time-based location management cost. From the result, when the time-based method is applied to location update, we can get the optimal time-interval which minimizes the location management cost.

• 한국경영과학회지
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• 제31권3호
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• pp.81-96
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• 2006

We consider a rental company that dynamically manages Its capacity level through capacity addition and return While serving customer with its own capacity, the company expands its capacity by renting items from an outside source so that it can avoid lost opportunities of rental which occur when stock is not sufficient. If stock becomes sufficiently large enough to cope with demands, the company returns expanded capacity to the outside source. Formulating the model into a Markov decision problem, we identify an optimal capacity management Policy which states when the company should expand its capacity and when it should return expanded capacity after capacity addition. Since it is intractable to analytically find the optimal capacity management policy and the optimal size of capacity expansion, we present a numerical procedure that finds these optimal values based on the value iteration method. Numerical analysis is implemented and we observe monotonic properties of the optimal performance measures by system parameters, which are meaningful in developing effective heuristic policies.

• 품질경영학회지
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• 제36권1호
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• pp.40-48
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• 2008

The purpose of this study is to rationally manage service facilities of convention center. This study is to develop the algorithm to consider optimal assignment and optimal operation system planning for convention center. The scheduling algorithm of this study develops through constructing the mathematical model and analyzing the mathematical structure of variables and constraints in model. The scheduling algorithm develops to consist eight stage of optimal operation planning and five stage of optimal assignment planning. Especially, this study indicates that optimum answer through mathematical model and results of algorithm is nondiscrimination.

• Management Science and Financial Engineering
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• 제19권2호
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• pp.43-47
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• 2013

This paper studies an optimal consumption and portfolio choice problem for unemployed people who have an option to work. Our problem is to find optimal consumption, risky investment, and workforce re-entry strategies for the unemployed. We find a closed form of the critical wealth level to re-enter the workforce. We show that the unemployed with a higher disutility of labor or a larger relative risk aversion are more reluctant to re-enter the workforce.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.24-29
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• 1996

If the LP problem doesn't have the optimal soultion uniquely, the solution fo the primal-dual barrier method converges to the interior point of the optimal face. Therefore, when the optimal vertex solution or the optimal basis is required, we have to perform the additional procedure to recover the optimal basis from the final solution of the interior point method. In this paper the exisiting methods for recovering the optimal basis or identifying the optimal solutions are analyzed and the new methods are suggested. This paper treats the two optimal basis recovery methods. One uses the purification scheme and the simplex method, the other uses the optimal face solutions. In the method using the purification procedure and the simplex method, the basic feasible solution is obtained from the given interior solution and then simplex method is performed for recovering the optimal basis. In the method using the optimal face solutions, the optimal basis in the primal-dual barrier method is constructed by intergrating the optimal solution identification technique and the optimal basis extracting method from the primal-optimal soltion and the dual-optimal solution.

• International Journal of Automotive Technology
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• 제8권6호
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• pp.791-798
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• 2007

The hydraulic hybrid vehicle(HHV) is an application of hydrostatic transmission technology to improve vehicle fuel economy and emissions. A relatively lower energy density of hydraulic accumulator and complicated coordinating operations between two power sources require a special energy management strategy to maximize the fuel saving potential. This paper presents a new type of configuration for parallel HHV to minimize the disadvantages of the hydraulic accumulator, as well as a methodology for developing an energy management strategy tailored specially for PHHV. Based on an analysis of the optimal energy distribution between two power sources over a representative urban driving cycle with a Dynamic Programming(DP) algorithm, a fuzzy-based optimal torque management strategy is designed and developed to control the torque distribution. Simulation results demonstrates that the optimal torque management strategy maximizes the advantages of this hybrid type of configuration, and the high power density characteristics of hydraulic technology effectively improve the robustness of the energy management strategy and fuel economy of the PHHV.

• 수산경영론집
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• 제33권2호
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• pp.31-48
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• 2002

This paper is aimed to analyze how to evaluate the choice of optimal management measures and level of control in fisheries management under the costly and imperfect management system by comparing with costless and perfect management system that is commonly assumed in the analysis of fisheries regulations. Fishermen would set the level of fishing efforts at the point where the marginal fishing profit for fishing effort is equal to the marginal level of fine under costly and imperfect management system. Therefore, under the case where the marginal fishing profit is higher than the marginal level of fine, the level of fishing efforts would be made at the point which is higher than the level of fishing efforts made under costless and perfect management system and is not a point where the economic profit is maximized in regulated fisheries. From this conclusion, the fishermens avoidance activities against regulations as well as the level of control in fisheries management substantially have an influence on the choice of fisheries management instruments. According to the analysis of optimal fisheries management policy, the economic profits in regulated fisheries are determined by the level of fisheries enforcement costs and total fishing profits, in which as enforcement costs increase the economic profits decrease. In addition, the economic profits vary in response to the level of control in avoidance activities. That is, as avoidance costs decrease, the economic profits increase. The determination of optimal level of control in fisheries management should be made at the point where the marginal regulation costs are equal to the marginal profits from regulated fisheries, in which marginal regulation costs are different according to the type of management measures. And the level of profits changes in response to different levels of avoidance activities. The management measure that can maximize the difference between the marginal regulation costs and marginal profits from regulated fisheries should be chosen as an optimal fisheries management instrument.

• Smart Structures and Systems
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• 제30권6호
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• pp.571-582
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• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.213-216
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• 2005

In this research, we explore how to manage the transition of technology generations considering incremental innovation of the existing technology generation. Firms can slow down decaying of the existing technology by continuous incremental improvements rather than introducing a new generation technology at the first time if the former strategy is better. We characterize optimal technology transition problem by setting up an optimal control model. The model which is originally designed and solved by Thompson(1968) as a ‘Machine maintenance problem’ has been cited to build the main body of our model. With this analytical model, we derive optimal ‘incremental innovation’ strategy which is considering transition to the next technology. Our analysis indicates that there exists an unique ‘stopping incremental innovation timing’. Before the point of time, the decision maker should make his effort at a maximum level to enhance the current technology. However from the stopping timing to the final time horizon where the new technology is introduced, it is found that not to invest to the current technology any more is optimal.