• The Journal of Information Systems
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• v.25 no.4
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• pp.105-119
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• 2016

Purpose The conventional solution methods for production scheduling problems typically focus on the active schedules, which result in short makespans. However, the active schedules are more difficult to generate than the semi active schedules. In other words, semi active schedule based search strategy may help to reduce the computational costs associated with production scheduling. In this context, this paper aims to compare the performances of active schedule based and semi active schedule based search methods for production scheduling problems. Design/methodology/approach Two decoding approaches, active schedule decoding and semi active schedule decoding, are introduced in this paper, and they are used to implement genetic algorithms for classical job shop scheduling problem. The permutation representation is adopted by the genetic algorithms, and the decoding approaches are used to obtain a feasible schedule from a sequence of given operations. Findings The semi active schedule based genetic algorithm requires slightly more iterations in order to find the optimal schedule, while its execution time is quite shorter than active schedule based genetic algorithm. Moreover, the operations of semi active schedule decoding is easy to understand and implement. Consequently, this paper concludes that semi active schedule based search methods also can be useful if effective search strategies are given.

• The Journal of Information Technology
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• v.3 no.2
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• pp.73-85
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• 2000

The efficient algorithms are suggested in this study for solving the multicommodity network flow problems applied to Communications Systems. These problems are typical NP-complete optimization problems that require integer solution and in which the computational complexity increases numerically in appropriate with the problem size. Although the suggested algorithms are not absolutely optimal, they are developed for computationally efficient and produce near-optimal and primal integral solutions. We supplement the traditional Lagrangian method with a price-directive decomposition. It proceeded as follows. First, A primal heuristic from which good initial feasible solutions can be obtained is developed. Second, the dual is initialized using marginal values from the primal heuristic. Generally, the Lagrangian optimization is conducted from a naive dual solution which is set as ${\lambda}=0$. The dual optimization converged very slowly because these values have sort of gaps from the optimum. Better dual solutions improve the primal solution, and better primal bounds improve the step size used by the dual optimization. Third, a limitation that the Lagrangian decomposition approach has Is dealt with. Because this method is dual based, the solution need not converge to the optimal solution in the multicommodity network problem. So as to adjust relaxed solution to a feasible one, we made efficient re-allocation heuristic. In addition, the computational performances of various versions of the developed algorithms are compared and evaluated. First, commercial LP software, LINGO 4.0 extended version for LINDO system is utilized for the purpose of implementation that is robust and efficient. Tested problem sets are generated randomly Numerical results on randomly generated examples demonstrate that our algorithm is near-optimal (< 2% from the optimum) and has a quite computational efficiency.

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.411-417
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• 2017

Environmental and growth factors such as light intensity, vapor pressure deficit, and leaf area index are important variables that can change the transpiration rate of plants. The objective of this study was to compare the transpiration rates estimated by modified Penman-Monteith model and artificial neural network. The transpiration rate of paprika (Capsicum annuum L. cv. Fiesta) was obtained by using the change in substrate weight measured by load cells. Radiation, temperature, relative humidity, and substrate weight were collected every min for 2 months. Since the transpiration rate cannot be accurately estimated with linear equations, a modified Penman-Monteith equation using compensated radiation (Shin et al., 2014) was used. On the other hand, ANN was applied to estimating the transpiration rate. For this purpose, an ANN composed of an input layer using radiation, temperature, relative humidity, leaf area index, and time as input factors and five hidden layers was constructed. The number of perceptons in each hidden layer was 512, which showed the highest accuracy. As a result of validation, $R^2$ values of the modified model and ANN were 0.82 and 0.94, respectively. Therefore, it is concluded that the ANN can estimate the transpiration rate more accurately than the modified model and can be applied to the efficient irrigation strategy in soilless cultures.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.1-22
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• 2018

The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

• Management & Information Systems Review
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• v.37 no.2
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• pp.87-108
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• 2018

This article explores the international trade flow of Bangladesh's ready-made garments (RMG). We first suggest the brief history and an international structure of trade among countries by using the trade volume. Then we implemented a gravity model regression with the sample of 38 major partner countries in order to investigate the potential export market for the RMG industry. The fixed effect and random effect model for the panel data during the period of 1990 to 2011 are estimated. Our result shows that Bangladesh's RMG exports are affected positively by the size of economy, inflation, exchange rate, foreign direct investment(FDI) and trade openness. On the other hand, the distance between trading partners are related negatively with the trade volume. We used the estimated coefficients from the panel regression in order to predict RMG export potential of Bangladesh. This might show which country is the promising export market for Bangladesh RMG industry. We found that Bangladesh has the highest potential of RMG export with Japan and USA, which seem to have considerable room for export growth if trade barriers and constraints are removed. We added some policy implications for encouraging the RMG export of Bangladesh by using the results from the analysis.

• Journal of the Korean Regional Science Association
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• v.33 no.4
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• pp.3-17
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• 2017

This study ranks by developing an urban competitiveness index of major global cities, including seven cities in Korea using data from the Global Cities Forecast (2013) provided by Oxford Economics. The City competitiveness index is selected from 18 indicators including scale index, ratio index, growth rate index while Gini coefficient is used for distribution index. In order to analyze the relationship between the competitiveness index and the distribution index, we use the LOGIT panel regression model. As a result, the increase in income inequality (Gini coefficient) has a negative effect on the economic growth rate in 5-year time lag shown statistically significant. We have compiled global rankings of 770 city competitiveness based upon 19 indicators by combining the global competitiveness index and the distribution index. The trend of rank shows that 7 Metropolitan Korean Cities are expected to decline substantially over the period. In particular, Seoul ranked $59^{th}$ in 2010 and $74^{th}$ in 2015. Its ranking is expected to be decline to $185^{th}$ in 2030. The declining competitiveness of Korean cities is expected to lead to a weakening of Korea's national competitiveness in the long run. Accordingly, it is imperative to identify problems and seek strategic plans to secure global urban competitiveness.

• Journal of the Korean Society of Radiology
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• v.10 no.7
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• pp.521-529
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• 2016

Since Gamma Knife(R) radiosurgery(GKRS) is based on a single-fraction high dose treatment strategy, independent verification for the results of Leksell GammaPlan(R) (LGP) is an important procedure in assuring patient safety and minimizing the risk of treatment errors. Several verification methods have been developed and reported previously. Thus these methods were tested statistically and tried on Leksell Gamma Knife(LGK) target treatments through the embodiment of the previously proposed algorithms(PPA). The purpose of this study was to apply and evaluate the accuracy of verification methods for LGK target treatments using PPA. In the study 10 patients with intracranial lesion treated by GKRS were included. We compared the data from PPA and LGP in terms of maximum dose, arbitrary point dose, and treatment time at the isocenter locations. All data were analyzed by Paired t-test, which is statistical method used to compare two different measurement techniques. No statistical significance in maximal dose at 10 cases was observed between PPA and LGP. Differences in average maximal dose ranged from -0.53 Gy to 3.71 Gy. The arbitrary point dose calculated by PPA and LGP was not statistically significant too. But we found out the statistical difference with p=0.021 between TMR and LGP for treatment time at the isocenter locations. PPA can be incorporated as part of a routine quality assurance(QA) procedure to minimize the chance of a wrong overdose. Statistical analyses demonstrated that PPA was in excellent agreement with LGP when considering the maximal dose and the arbitrary point dose for the best plan of GKRS. Due to the easy applicability we hope PPA can be widely used.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.2
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• pp.174-188
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• 2004

In the life environment changed with not only the quality and the price of the products but also the material abundance, it is the most crucial factor for the strategy of product sales to investigate consumer's sensibility and preference degree. In this perspective, it is necessary to design and merchandise the products in cope with each consumer's sensibility and needs as well as its functional aspects. In this paper, we propose the Fashion Design Recommender Agent System (FDRAS-pro) for textile design applying collaborative filtering personalization technique as one of the methods of material development centered on consumer's sensibility and preference. For a collaborative filtering system based on textile, Representative-Attribute Neighborhood is adopted to determine the number or neighbors that will be used for preferences estimation. Pearson's Correlation Coefficient is used to calculate similarity weights among users. We build a database founded on the sensibility adjectives to develop textile designs by extracting the representative sensibility adjectives from users' sensibility and preferences about textile designs. FDRAS-pro recommends textile designs to a customer who has a similar propensity about textile. To investigate the sensibility and emotion according to the effect of design factors, fertile designs were analyzed in terms of 9 design factors, such as, motif source, motif-background ratio, motif variation, motif interpretation, motif arrangement, motif articulation, hue contrast, value contrast, chroma contrast. Finally, we plan to conduct empirical applications to verify the adequacy and the validity of our system.

• Clean Technology
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• v.18 no.1
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• pp.69-75
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• 2012

In this study, we executed an environmental impact assessment about recycling of ITO (Indium Tin Oxide), used for touch panel. ITO is mainly used to make transparent conductive coatings for touch and flat screen LCD (Liquid Crystal Display), ELD (Emitting Light Device), PDP (Plasma Display Panel). This demand is increasing little by little. but form current status, ITO is discarded than recycling. It is important to recycling ITO for national strategies about resource conservation, and reduce environmental burden. Also Landfill or incineration of ITO cloud be harmful to the human health in the long-term. Material Life Cycle Assessment method (MLCA) was conducted for comparison landfill and recycling of ITO. MLCA would provide more information for environmental issues and potential environmental impacts of ITO. The study includes two scenarios, the basic scenario is recycling of ITO (10, 20, 30%) and the other scenario is landfill of ITO. In addition, amount of carbon dioxide and energy were calculated.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.5
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• pp.385-392
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• 2013

The finite element method has become the most widely used method of structural analysis and recently, the method has often been applied to complex dynamic and nonlinear structural analyses problems. Even for these complex problems, where the responses are hard to predict, finite element analyses yield reliable results if appropriate element types and meshes are used. However, the dynamic and nonlinear behaviors of a structure often include large deformations in various portions of the structure and if the same mesh is used throughout the analysis, some elements may deform to shapes beyond the reliable limits; thus dynamically adapting finite element meshes are needed in order for the finite element analyses to be accurate. In addition, to satisfy the users requirement of quick real run time of finite element programs, the algorithms must be computationally efficient. This paper presents an adaptive finite element mesh generation scheme for dynamic analyses of structures that may adapt at each time step. Representative strain values are used for error estimates and combinations of the h-method(node movement) and the r-method(element division) are used for mesh refinements. A coefficient that depends on the shape of an element is used to limit overly distorted elements. A simple frame example shows the accuracy and computational efficiency of the scheme. The aim of the study is to outline the adaptive scheme and to demonstrate the potential use in general finite element analyses of dynamic and nonlinear structural problems commonly encountered.