• IE interfaces
• /
• v.13 no.3
• /
• pp.378-387
• /
• 2000

As the globalization of manufacturing companies continues, the scope of dependence between these companies and distributors, and other suppliers are growing very rapidly since no one company manufactures or distributes the whole product by themselves. And, the need to increase the efficiency of the whole supply chain is increasing. This paper deals with a multi-plant lot-sizing problem(MPLSP) which happens in a decentralized manufacturing system of a supply chain. In this study, we assume that the whole supply chain is driven by a single source of independent demand and many levels of dependent demands among manufacturing systems in the supply chain. We consider setup cost, transportation cost and time, and inventory holding cost as a decision factor in the MPLSP. The MPLSP is decomposed into two sub-problems: a planning problem of the whole supply chain and a lot-sizing problem of each manufacturing system. The supply chain planning problem becomes a pure linear programming problem and a Generalized Goal Decomposition method is used to solve the problem. Its result is used as a goal of the lot-sizing problem. The lot-sizing problem is solved using the CPLEX package, and then the coefficients of the planning problem are updated reflecting the lot-sizing solution. This procedure is repeated until termination criteria are met. The whole solution process is similar to Lagrangian relaxation method in the sense that the solutions are approaching the optimum in a recursive manner. Through experiments, the proposed closed-loop hierarchical planning and traditional hierarchical planning are compared to optimal solution, and it is shown that the proposed method is a very viable alternative for solving production planning problems of decentralized manufacturing systems and in other areas.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.4
• /
• pp.493-498
• /
• 2004

A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.

• Journal of The Korea Institute of Healthcare Architecture
• /
• v.22 no.4
• /
• pp.47-55
• /
• 2016

Purpose: Growth and change are the most important things in planning of hospital architecture. It is especially necessary for countless changes taken place since the hospital opens to be adapted to the planning of hospital architecture phase. The space depth in the hospital serves a very crucial role in accepting these changes. The purpose of this study is to provide basic data necessary to space depth planning to prepare for change through analyzing space depth's change in hospital architecture chronologically. Methods:: The method of this study is analyzing space depth's change in cases of 19 hospitals in total, from the 1980's, which is the quantitative growth period, until recently. Especially this study is analyzing Max & Min space depth focusing change of medical environment. Based on this, this study suggests an form of space depth and optimum range of space depth response to growth and change of hospital architecture. Results: The conclusions of this study are as follows. Considering these conclusion, double linear system is most appropriate for space depth for hospital architecture planning focused on system. Optimal range of space depth is at least 21.6m or more in case of clinic room and from 27 meter to 37meter in case of examination & treatment room. Implications: Space of Depth is a key element determining system for hospital architecture planning focused on system. The results of this paper can be data for planning system of hospital architecture which copes with the change.

• Journal of radiological science and technology
• /
• v.45 no.6
• /
• pp.491-502
• /
• 2022

The purpose of this study was to retrospectively investigate the upper and lower control limits of treatment planning parameters using EBT film based delivery quality assurance (DQA) results and to analyze the results of statistical process control (SPC) in helical tomotherapy (HT). A total of 152 patients who passed or failed DQA results were retrospectively included in this study. Prostate (n = 66), rectal (n = 51), and large-field cancer patients, including lymph nodes (n = 35), were randomly selected. The absolute point dose difference (DD) and global gamma passing rate (GPR) were analyzed for all patients. Control charts were used to evaluate the upper and lower control limits (UCL and LCL) for all the assessed treatment planning parameters. Treatment planning parameters such as gantry period, leaf open time (LOT), pitch, field width, actual and planning modulation factor, treatment time, couch speed, and couch travel were analyzed to provide the optimal range using the DQA results. The classification and regression tree (CART) was used to predict the relative importance of variables in the DQA results from various treatment planning parameters. We confirmed that the proportion of patients with an LOT below 100 ms in the failure group was relatively higher than that in the passing group. SPC can detect QA failure prior to over dosimetric QA tolerance levels. The acceptable tolerance range of each planning parameter may assist in the prediction of DQA failures using the SPC tool in the future.

• Korean Journal of Community Nutrition
• /
• v.21 no.4
• /
• pp.332-343
• /
• 2016

Objectives: Study purpose was to investigate perception on diet, diet problems and related factors among young adult women using focus group interviews (FGI) based on the Social Cognitive Theory (SCT). Methods: Eight groups of FGI were conducted with 47 female undergraduate or graduate students. Guide for FGI included questions regarding perception on optimal diet, diet problems and cognitive, behavioral, and environmental factors of SCT. FGI were video, audio-taped, transcribed and analyzed by themes and sub-themes. Results: Subjects showed irregular eating habits (skipping breakfast, irregular meal time) and selection of unhealthy foods as the main diet problems. Regarding cognitive factors related to optimal diet, subjects mentioned positive outcome expectations (e.g., health promotion, skin health, improvement in eating habits, etc.) and negative outcome expectations (e.g., annoying, hungry, expensive, taste). Factors that promoted optimal diet were mainly received from information from mobile or internet and access to menu or recipes. Factors that prevented optimal diet included influence from friends, lack of time and cooking skills. Behavioral factors for optimal diet included behavioral capability regarding snacks, healthy eating and smart food selection. Subjects mentioned mass media (mobile, internet, TV) as the influential physical environment, and significant others (parents, friends, grandparents) as the influential social environment in optimal diet. For education topics, subjects wanted to learn about healthy meals, basic nutrition, disease and nutrition, and weight control. They wanted to learn those aspects by using mobile or internet, lectures (cooking classes), campaign and events. Conclusions: Study results might be used for planning education regarding optimal diet for young adult women. Education programs need to focus on increasing positive outcome expectations (e.g., health) and behavioral capability for healthy eating and food selection, reducing negative outcome expectations (e.g., cost, taste) and barriers, making supportive environments for optimal diet, and incorporating topics and methods found in this study.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.6
• /
• pp.674-680
• /
• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.9
• /
• pp.2191-2198
• /
• 2013

This paper proposes a RFID cell planning scheme for indoor location-awareness. We theoretically develop four objective functions that yield objective goals significant to the optimal design of a RFID cell topology and simulation is conducted to evaluate the performance of the proposed RFID cell planning scheme. We also evaluate the performance of the proposed technique after practically installing RFID readers in an indoor space to configure a RFID cell topology. Performance evaluations are conducted in terms of the following objective goals: minimal number of RFID readers for configuring a RFID cell topology, maximal RFID cell coverage areas for indoor location-awareness, minimal overlapping cells, and maximal indoor location-awareness accuracy.

• Journal of Korean Institute of Industrial Engineers
• /
• v.28 no.1
• /
• pp.14-24
• /
• 2002

We focus on resource allocation planning in container terminal operation planning problems and present network design model and genetic algorithm. We present a network design model in which arc capacities must be properly dimensioned to sustain the container traffic. This model supports various planning aspects of container terminal and brings in a very general form. The integer programming model of network design can be extended to accommodate vertical or horizontal yard configuration by adding constraints such as restricting the sum of yard cranes allocated to a block of yards. We devise a genetic algorithm for the network design model in which genes have the form of general integers instead of binary integers. In computational experiments, it is found that the genetic algorithm can produce very good solution compared to the optimal solution obtained by CPLEX in terms of computation time and solution quality. This algorithm can be used to generate many alternatives of a resource allocation plan for the container terminal and to evaluate the alternatives using various tools such as simulation.

• Journal of the Korea Society for Simulation
• /
• v.15 no.3
• /
• pp.39-47
• /
• 2006

In most of supply chain planning practices, the estimated demands, which are forecasted for each individual period in a forecasting window, are regarded as deterministic. But, in reality, the forecasted demands for the periods of a given horizon are stochastically distributed. Instead of using a safety stock, this study considers a direct control of service level by choosing the demand used in planning from the distributed forecasted demand values for the corresponding period. Using the demand quantile and echelon stock concept, we propose a simple but efficient heuristic algorithm for multi-echelon serial systems under service level constraints. Through a comprehensive simulation study, the proposed algorithm was shown to be very accurate compared with the optimal solutions.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.4
• /
• pp.405-413
• /
• 2006

A novel approach based on genetic algorithms (GA) is developed to find a global minimum-jerk trajectory of a space robotic manipulator in joint space. The jerk, the third derivative of position of desired joint trajectory, adversely affects the efficiency of the control algorithms and stabilization of whole space robot system and therefore should be minimized. On the other hand, the importance of minimizing the jerk is to reduce the vibrations of manipulator. In this formulation, a global genetic-approach determines the trajectory by minimizing the maximum jerk in joint space. The planning procedure is performed with respect to all constraints, such as joint angle constraints, joint velocity constraints, joint angular acceleration and torque constraints, and so on. We use an genetic algorithm to search the optimal joint inter-knot parameters in order to realize the minimum jerk. These joint inter-knot parameters mainly include joint angle and joint angular velocities. The simulation result shows that GA-based minimum-jerk trajectory planning method has satisfactory performance and real significance in engineering.