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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal DOI :
Korean Institute of Industrial Engineers
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Volume & Issues
Volume 24, Issue 4 - Dec 2011
Volume 24, Issue 3 - Sep 2011
Volume 24, Issue 2 - Jun 2011
Volume 24, Issue 1 - Mar 2011
Selecting the target year
Operating Room Reservation Problem Considering Patient Priority : Modified Value Iteration Method with Binary Search
Min, Dai-Ki ;
IE interfaces, volume 24, issue 4, 2011, Pages 274~280
DOI : 10.7232/IEIF.2011.24.4.274
Delayed access to surgery may lead to deterioration in the patient condition, poor clinical outcomes, increase in the probability of emergency admission, or even death. The purpose of this work is to decide the number of patients selected from a waiting list and to schedule them in accordance with the operating room capacity in the next period. We formulate the problem as an infinite horizon Markov Decision Process (MDP), which attempts to strike a balance between the patient waiting times and overtime works. Structural properties of the proposed model are investigated to facilitate the solution procedure. The proposed procedure modifies the conventional value iteration method along with the binary search technique. An example of the optimal policy is provided, and computational results are given to show that the proposed procedure improves computational efficiency.
Metaheuristics of the Rail Crane Scheduling Problem
Kim, Kwang-Tae ; Kim, Kyung-Min ;
IE interfaces, volume 24, issue 4, 2011, Pages 281~294
DOI : 10.7232/IEIF.2011.24.4.281
This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.
Asset Buying Problem with Consideration of the Budget Constraints and Loan
Son, Jae-Dong ;
IE interfaces, volume 24, issue 4, 2011, Pages 295~303
DOI : 10.7232/IEIF.2011.24.4.295
This paper presents a discrete time optimal asset buying problem with a predetermined final deadline where an available budget is limited. A cost is paid to search for assets called the search cost. A seller who shows up offers a price for the asset and then the buyer decides whether or not to buy the asset by comparing the offered price to his optimal selection threshold. When the budget becomes less than the search cost or the price of the asset the buyer can get a necessary loan with some interests. We clarify the properties of the buyer`s optimal selection threshold in order to maximize the expected value of budget which is left after paying all the search costs and the price of the asset at that point in time.
A Path Planning to Maximize Survivability for Unmanned Aerial Vehicle based on 3-dimensional Environment
Kim, Ki-Tae ; Jeon, Geon-Wook ;
IE interfaces, volume 24, issue 4, 2011, Pages 304~313
DOI : 10.7232/IEIF.2011.24.4.304
An Unmanned Aerial Vehicle(UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are currently employed in many military missions(surveillance, reconnaissance, communication relay, targeting, strike etc.) and a number of civilian applications(communication service, broadcast service, traffic control support, monitoring, measurement etc.). For accomplishing the UAV`s missions, guarantee of survivability should be preceded. The main objective of this study is the path planning to maximize survivability for UAV based on 3-dimensional environment. A mathematical programming model is suggested by using MRPP(Most Reliable Path Problem) and solved by transforming MRPP into SPP(Shortest Path Problem). This study also suggests a
algorithm based on 3-dimensional environment to UAV`s path planning. According to comparison result of the suggested algorithm and SPP algorithms (Dijkstra,
algorithm), the suggested algorithm gives better solution than SPP algorithms.
Empirical Analysis of DEA models Validity for R&D Project Performance Evaluation : Focusing on Rank Correlation with Normalization Index
Park, Sung-Min ;
IE interfaces, volume 24, issue 4, 2011, Pages 314~322
DOI : 10.7232/IEIF.2011.24.4.314
This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is `sales per R&D project fund` which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU`s) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman`s
are investigated in addition to Pearson`s
. With an up-to-date empirical massive dataset of n
Predicting the Score of a Soccer Match by Use of a Markovian Arrival Process
Kim, Nam-Ki ; Park, Hyun-Min ;
IE interfaces, volume 24, issue 4, 2011, Pages 323~329
DOI : 10.7232/IEIF.2011.24.4.323
We develop a stochastic model to predict the score of a soccer match. We describe the scoring process of the soccer match as a markovian arrival process (MAP). To do this, we define a two-state underlying Markov chain, in which the two states represent the offense and defense states of the two teams to play. Then, we derive the probability vector generating function of the final scores. Numerically inverting this generating function, we obtain the desired probability distribution of the scores. Sample numerical examples are given at the end to demonstrate how to utilize this result to predict the final score of the match.
A Comparative Study on Efficiency of Technologically Innovative Activities between Manufacturing and Service Industries Using DEA
Suh, Yong-Yoon ; Kim, Moon-Soo ;
IE interfaces, volume 24, issue 4, 2011, Pages 330~340
DOI : 10.7232/IEIF.2011.24.4.330
This research aims at conducting a comparative study on the relative efficiency of technologically innovative activities between manufacturing and service industries using data envelopment analysis (DEA). First, as an individual approach, efficiency of technologically innovative activities between manufacturing and service industries is separately evaluated. The results show that efficiency of both industries is similarly low, but patterns of technologically innovative activities differ from each other. Manufacturing industries usually do innovation focusing on various outputs with a single input, whereas service industries tend to do innovation emphasizing on a single output with mixed inputs. Second, as a holistic approach to both industries, efficiency is collectively assessed. The analysis demonstrates that efficiency of service industries is higher than that of manufacturing industries, and there are similar patterns of technologically innovative activities between both manufacturing and service industries. This study provides industrial managers with policy implications based on similarities and differences between manufacturing and service industries.
Optimizing Zone-dependent Two-level Facility Location Problem
Lim, Sung-Hoon ; Sung, Chang-Sup ; Song, Sang-Hwa ;
IE interfaces, volume 24, issue 4, 2011, Pages 341~350
DOI : 10.7232/IEIF.2011.24.4.341
This paper considers a problem of locating both distribution centers and retailers in a zone-dependent two-level distribution network where either a distribution center or a retailer should be located in each zone. Customer demands of each zone should be satisfied directly from either its own distribution center or its own retailer being supplied from a distribution center of another zone. The objective of the proposed problem is to minimize total cost being composed of distribution center/retailer setup costs and transportation costs. In the analysis, the problem is proved to be NP-hard, so that a branch-and-bound algorithm is derived for the problem. Numerical experiments show that the proposed branch-and-bound algorithm provides the optimal solution efficiently for some small problems.
Electricity Demand Forecasting based on Support Vector Regression
Lee, Hyoung-Ro ; Shin, Hyun-Jung ;
IE interfaces, volume 24, issue 4, 2011, Pages 351~361
DOI : 10.7232/IEIF.2011.24.4.351
Forecasting of electricity demand have difficulty in adapting to abrupt weather changes along with a radical shift in major regional and global climates. This has lead to increasing attention to research on the immediate and accurate forecasting model. Technically, this implies that a model requires only a few input variables all of which are easily obtainable, and its predictive performance is comparable with other competing models. To meet the ends, this paper presents an energy demand forecasting model that uses the variable selection or extraction methods of data mining to select only relevant input variables, and employs support vector regression method for accurate prediction. Also, it proposes a novel performance measure for time-series prediction, shift index, followed by description on preprocessing procedure. A comparative evaluation of the proposed method with other representative data mining models such as an auto-regression model, an artificial neural network model, an ordinary support vector regression model was carried out for obtaining the forecast of monthly electricity demand from 2000 to 2008 based on data provided by Korea Energy Economics Institute. Among the models tested, the proposed method was shown promising results than others.
A Genetic Algorithm for the Container Pick-Up Problem
Lee, Shi-W. ;
IE interfaces, volume 24, issue 4, 2011, Pages 362~372
DOI : 10.7232/IEIF.2011.24.4.362
Container pick-up scheduling problem is to minimize the total container handling time, which consists of the traveling distance and the setup time of yard cranes in a container yard. Yard cranes have to pick-up the containers which are stacked in the yard-bays to satisfy the work schedule requirement of quay crane, which loads and unloads containers on or from container ships. This paper allows the movement of multiple yard cranes among storage blocks. A mixed integer programming model has been formulated and a genetic algorithm (GA) has been proposed to solve problems of large sizes. Computational results show that the proposed GA is an effective method.
Heat Demand Forecasting for Local District Heating
Song, Ki-Burm ; Park, Jin-Soo ; Kim, Yun-Bae ; Jung, Chul-Woo ; Park, Chan-Min ;
IE interfaces, volume 24, issue 4, 2011, Pages 373~378
DOI : 10.7232/IEIF.2011.24.4.373
High level of accuracy in forecasting heat demand of each district is required for operating and managing the district heating efficiently. Heat demand has a close connection with the demands of the previous days and the temperature, general demand forecasting methods may be used forecast. However, there are some exceptional situations to apply general methods such as the exceptional low demand in weekends or vacation period. We introduce a new method to forecast the heat demand to overcome these situations, using the linearities between the demand and some other factors. Our method uses the temperature and the past 7 days` demands as the factors which determine the future demand. The model consists of daily and hourly models which are multiple linear regression models. Appling these two models to historical data, we confirmed that our method can forecast the heat demand correctly with reasonable errors.
A Study on Electrical Power Trading in Minimum Price Wholesale Market
Seo, Tae-Min ; Lee, Hee-Sang ;
IE interfaces, volume 24, issue 4, 2011, Pages 379~386
DOI : 10.7232/IEIF.2011.24.4.379
The importance of renewable energy technology is discussed and next generation power transmission networks, which is called the smart grid, are constructed in developed countries. However for construction and operation of the smart grid, it is required not only to develop the electrical power generation technologies and transmission equipments but also to study systematic analysis and optimization for design and operation of the smart grid. In this paper we study electrical power trade in the smart grid using operations research models and simulation methods. We also consider future electrical power exchange markets in Korea and build four scenarios and the related optimization and simulation models, which reflect electrical power transaction pricing strategies of stake-holders. We can also simulate electrical power exchange market and analyze the results of electrical power trading, which can give us some insights for future electrical power exchange market.
Analysis of Task and Postures of Retail Grocery Store Workers
Hwang, Jae-Jin ; Lee, In-Seok ; Kim, Hyun-Joo ; JungChoi, Kyung-Hee ; Bahk, Jin-Wook ; Jung, Myung-Chul ;
IE interfaces, volume 24, issue 4, 2011, Pages 387~395
DOI : 10.7232/IEIF.2011.24.4.387
This study was aiming to examine work time, frequency, work environment, and postures of retail grocery store workers to evaluate the risk of musculoskeletal disorders. An ergonomic evaluation was conducted using job analysis and posture analysis. The four most time-consuming tasks were inspecting (27.4%), arranging (21.4%), cutting (17.6%), and displaying (15.6%). The height and length of the shelves evaluated in the field was inappropriate for workers. The most common posture was a standing posture with neutral back, and bent head, right upper arm, lower arms, and hands. Finally, this paper concluded that `arranging,` `cutting,` and `displaying` seemed more stressful than other operations. The result of the ergonomic evaluation would contribute to design a better workspace in ergonomics.
Optimal Control for Cash Management with Investment and Retrieval
Kim, Eun-Gab ; Byun, Jin-Ho ; Pae, Jae-Hyun ;
IE interfaces, volume 24, issue 4, 2011, Pages 396~407
DOI : 10.7232/IEIF.2011.24.4.396
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.
Real Option Decision Tree Models for R&D Project Investment
Choi, Gyung-Hyun ; Cho, Dae-Myeong ; Joung, Young-Ki ;
IE interfaces, volume 24, issue 4, 2011, Pages 408~419
DOI : 10.7232/IEIF.2011.24.4.408
R&D is a foundation for new business chance and productivity improvement leading to enormous expense and a long-term multi-step process. During the R&D process, decision-makers are confused due to the various future uncertainties that influence economic and technical success of the R&D projects. For these reasons, several decision-making models for R&D project investment have been suggested; they are based on traditional methods such as Discounted Cash Flow (DCF), Decision Tree Analysis (DTA) and Real Option Analysis (ROA) or some fusion forms of the traditional methods. However, almost of the models have constraints in practical use owing to limits on application, procedural complexity and incomplete reflection of the uncertainties. In this study, to make the constraints minimized, we propose a new model named Real Option Decision Tree Model which is a conceptual combination form of ROA and DTA. With this model, it is possible for the decision-makers to simulate the project value applying the uncertainties onto the decision making nodes.
Development and Application of an Anthropometric Design Method Considering Physical Human Variabilities
Jung, Ki-Hyo ; Lee, Baek-Hee ; You, Hee-Cheon ;
IE interfaces, volume 24, issue 4, 2011, Pages 420~427
DOI : 10.7232/IEIF.2011.24.4.420
The present study developed an anthropometric design method accommodating physical human variabilities for user-centered product development. The proposed design method is based on the boundary zone method, a technique to generate a group of humanoids properly representing the body size diversity of thedesign target population. In addition, the anthropometric design method considers the variability of postures in the design process by incorporating the simulation of posture. The effectiveness of the proposed design method was evaluated in terms of multivariate accommodation percentage (MAP) by applying it to designing a computer workstation with 90% of accommodation percentage. The performance evaluation showed that the MAP (89%) of the computer workstation design produced by the proposed method was quite close to the designated accommodation percentage. The proposed design method can be of use to develop an effective anthropometric design for user-centered product development.
The Real Time Vehicles Tracking and Intelligent Transportation Management System Using Smart Phone Application
Kim, Sung-Gyun ; Byun, Hae-Gwon ; Yoo, Woo-Sik ; Choi, Jin-Suk ;
IE interfaces, volume 24, issue 4, 2011, Pages 428~434
DOI : 10.7232/IEIF.2011.24.4.428
In these days, mobile technology such as smart phone and GPS have an effect on business processes of many companies especially a transportation company. The purpose of this paper is to present the development processes of real time vehicles tracking and intelligent TMS (Transportation Management System) using smart phone applications. The objective of this study is two-fold. The first is to redesign business process of the transportation company. Using BPR (business process re-engineering), we analyze current processes to find opportunities for improvement redefining processes after adopting mobile technology precisely. The second is to develop the real time vehicles tracking and intelligent TMS. Proposed system consists of four parts : (1) intelligent TMS(web system) (2) real time vehicle tracking application for TMS (3) real time tracking application for customer (4) salesman supporting application. Developed system was tested at the transportation company and was found to be an useful system.
Development of a Delivery Workload Management System for Measuring and Balancing Standard Workload of Mailmen
Cha, Chun-Nam ; Sun, Ji-Ung ; Park, Moon-Sung ;
IE interfaces, volume 24, issue 4, 2011, Pages 435~446
DOI : 10.7232/IEIF.2011.24.4.435
Performance measures play a critical role in formulating mail delivery strategies and evaluating actual results. Nevertheless, the existing method and corresponding system to determine the standard workloads of mailmen is developed without careful consideration of real delivery environments and various requirements of mailmen. Hence, the current system is insufficient for optimal management of workloads and shows substantial gaps when compared to the results of actual work-site. This study considers how to improve the current workload management system of mailmen. We first performed the as-is analysis of the mail delivery service and then developed a prototype of advanced delivery workload management system. The to-be system consists of five subsystems which can be grouped into three categories; master data management, workloads management, performance analysis. Our results can be a valuable guide for the development of real system for measuring and balancing the workloads of mailmen.
A New Approach to Spatial Pattern Clustering based on Longest Common Subsequence with application to a Grocery
Jung, In-Chul ; Kwon, Young-S. ;
IE interfaces, volume 24, issue 4, 2011, Pages 447~456
DOI : 10.7232/IEIF.2011.24.4.447
Identifying the major moving patterns of shoppers` movements in the selling floor has been a longstanding issue in the retailing industry. With the advent of RFID technology, it has been easier to collect the moving data for a individual shopper`s movement. Most of the previous studies used the traditional clustering technique to identify the major moving pattern of customers. However, in using clustering technique, due to the spatial constraint (aisle layout or other physical obstructions in the store), standard clustering methods are not feasible for moving data like shopping path should be adjusted for the analysis in advance, which is time-consuming and causes data distortion. To alleviate this problems, we propose a new approach to spatial pattern clustering based on longest common subsequence (LCSS). Experimental results using the real data obtained from a grocery in Seoul show that the proposed method performs well in finding the hot spot and dead spot as well as in finding the major path patterns of customer movements.