• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.106-116
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• 2021

This paper considers a joint problem for blood inventory planning at hospitals and blood delivery planning from blood centers to hospitals, in order to alleviate the blood service imbalance between big and small hospitals being occurred in practice. The joint problem is to determine delivery timing, delivery quantity, delivery means such as medical drones and legacy blood vehicles, and inventory level to minimize inventory and delivery costs while satisfying hospitals' blood demand over a planning horizon. This problem is formulated as a mixed integer programming model by considering practical constraints such as blood lifespan and drone specification. To solve the problem, this paper employs a Lagrangian relaxation technique and suggests a time efficient Lagrangian heuristic algorithm. The performance of the suggested heuristic is evaluated by conducting computational experiments on randomly-generated problem instances, which are generated by mimicking the real data of Korean Red Cross in Seoul and other reliable sources. The results of computational experiments show that the suggested heuristic obtains near-optimal solutions in a shorter amount of time. In addition, we discuss the effect of changes in the length of blood lifespan, the number of planning periods, the number of hospitals, and drone specifications on the performance of the suggested Lagrangian heuristic.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.381-389
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• 2021

This study aims to examine the effect of strategic planning, human resource management, and asset management on increasing the productivity of the rural economy. This research is a quantitative approach. The research sample was carried out by simple random sampling and data collection using a questionnaire so that 129 respondents were determined. The research test was conducted using multiple linear regression with the OLS (Ordinary Least Square model. The results obtained were that strategic planning, human resource management, and asset management had a significant positive effect on increasing the productivity of the rural economy. This shows that strategic planning is the most important thing in industry, companies, or organizations as a guideline to achieve optimal performance. In addition, human resource management and asset management are positive supports for increasing the economic productivity of rural communities to achieve welfare goals. This research proves that strategic planning must be carried out by considering the existing potential, both sources. natural resources, human resources, and economic resources Meanwhile, human resource management and asset management are mandatory to support the sustainability of an organization or company so that the benefits of the study as study material in strategic decision making, both in business and public policy.

• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.545-552
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• 2006

The purpose of this study is to develop an optimal, long-term planning model for improvement of water distribution networks. The water distribution system is divided into sub-zones and the decision of improvement plan is made for each sub-zone. Costs for replacement, rehabilitation and repair, benefits including reduced pumping and leakage costs, and hydraulic reliability are considered to make optimal decision for improvement planning of water network. Harmony search algorithm is applied to optimize the system and hydraulic analysis model EPANET is interfaced with the optimal decision model to check the hydraulic reliability, The developed model is applied to actual water distribution system in Daegu-city, South Korea. The new model which use durability, conveyance and cost as a decision variable is different from existing methods which use only burying period and pipe type and can be used as optimal decision making system for water distribution network.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.5
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• pp.45-56
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• 2019

Urban green areas are generally composed of relatively small and fragmented patches, but it is a critical factor for the quality of an urban environment. They have positive effects such as increasing green connectivity, reducing runoff, and mitigating urban heat. But, there is a lack of urban greening plans that consider the comprehensive effects of green space in real urban areas. To fill this gap in this literature, this study identifies a planning model that determines the optimal locations for maximizing green areas' multiple effects(e.g., heat mitigation and enhancement of connectivity) by using unused lots. This model also considers minimizing costs using meta-heuristic optimization algorithms. As a results, we finds 50 optimal plans that considers two effects within the limited cost in Nowon-gu. The optimal plans show the trade-off effect between connectivity, heat mitigation and cost. They also show the critical unused land lots for urban greening that are commonly selected in various plans. These optimal plans can effectively inform quantitative effectiveness of green space and their trade-off. We expect that our model will contribute to the improvement of green planning processes in reality.

• Human Ecology Research
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• v.58 no.4
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• pp.539-560
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• 2020

This study presents work-family multiple-role planning by female university students as a new approach to worklife balance. Accordingly, this study examines university years as a key time frame during which students establish their career paths. This study integrates the social cognitive career theory and the planned behavior theory to design and evaluate a model that explains the work-family multiple-role planning process; in addition, it develops an optimal model to predict the intentions of female university students in work-family multiple-role planning. This study has conducted a structural survey with 500 female university students. After inspecting the data, the responses of 435 participants were used in the data analysis (SEM) with SPSS 21.0 and AMOS 21.0. The findings include the following. First, suitability of predictive model presents a satisfying fit. The major factors in this study's model (parental support, subjective norms, attitudes toward multiple-role planning, career decision self-efficacy, and outcome expectations) are verified as direct and indirect predictors of the work-family multiple-role planning intent of female university students. Second, the strongest predictive factor for the work-family multiple-role planning intent is the social environment factor (subjective norms), indicating that the influence of social pressure on intent is relatively large. The predictive model formulated under this study's integrated theoretical framework supplements existing research that focused on attitudes toward multiple-role planning as well as provides a more profound theoretical foundation on which work-family multiple-role planning behaviors can be better understood.

• Journal of Radiation Protection and Research
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• v.30 no.1
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• pp.17-25
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• 2005

Since the safety of nuclear power plant has been becoming a big social issue the exposure dose of radiation for workers has been one of the important factors concerning the safety problem. The existing calculation methods of radiation dose used in the planning of radiation work assume that dose rate does not depend on the location within a work space thus the variation of exposure dose by different work path is not considered. In this study, a modified numerical method was presented to estimate the exposure dose during radiation work in radwaste storage considering the effects of the distance between a worker and sources. And a new numerical algorithm was suggested to search the optimal work path minimizing the exposure dose in pre-defined work space with given radiation sources. Finally, a virtual work simulation program was developed to visualize the exposure dose of radiation doting radiation works in radwaste storage and provide the capability of simulation for work planning. As a numerical example, a test radiation work was simulated under given space and two radiation sources, and the suggested optimal work path was compared with three predefined work paths. The optimal work path obtained in the study could reduce the exposure dose for the given test work. Based on the results, tile developed numerical method and simulation program could be useful tools in the planning of radiation work.

• Journal of Korean Society for Quality Management
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• v.14 no.1
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• pp.61-66
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• 1986

Many papers have suggested various models how to decide an optimal time for replacing equipment. In this study, Dynamic Programming is applied to establish a model of replacing equipment and a new algorithm is developed for computerization to meet the increased number of variables. It is possible to predict the real situation with higher accuracy by employing the proposed model including more variables such as planning horizon, original cost, salvage value, decreasing rate, operating and maintenance costs, increasing rate, and so on.

• IE interfaces
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• v.2 no.1
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• pp.37-45
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• 1989

Guide path design is the most important factor in planning automated guided vehicle systems(AGVS) in manufacturing shop environments. This paper studies a heuristic procedure to design an optimal bi-directional guide path with the objective of the minimum total travel time of the vehicles. An example is solved to validate the procedure developed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1181-1184
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• 1996

As usual systems, robot manipulators have also physical constraints for operating. It is a difficult problem that we operate manipulator in the minimal time under these constraints. In this paper, we solve this problem dividing it into two steps. In the first step, we find the minimal time trajectories by optimizing qubic polynomial joint trajectories using evolutionary algorithms. In the second step, we optimize controller for robot manipulator to track precisely trajectories optimized in the previous step.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.191-193
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• 1989

This paper presents a optimal Var allocation algorithm for minimizing power loss and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A stochastic Linear Programming technique based on chance constrained method is applied to solve the probabilistic constraint. The test result in IEEE-14 Bus model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before Var allocation.