• Journal of Information Processing Systems
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• v.15 no.3
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• pp.655-669
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• 2019

Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.753-773
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• 2005

This paper is a study of the investment dynamics focusing on crude oil supply by OPEC and non-OPEC. Oil supply capacity is first determined by a leader, OPEC, and by an aggregate that represents non-OPEC producers. OPEC wants to increase a gain from oil price increase while keeping its market share relative to non-OPEC's share. An investment rule model is developed for OPEC crude oil supply capacity in response to non-OPEC's decision. In presence of oil price uncertainty, oil price threshold is derived above which it is optimal for OPEC to expand oil supply capacity since otherwise the increased supply of non-OPEC results in weakening of OPEC market share in the world oil market. In addition, a lower threshold price is derived below which OPEC triggers a capacity reduction to regain its otherwise forgone profits. A simulation is provided for calculating the capacity expansion and reduction thresholds.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.344-350
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• 2024

A Reference Sound Source (RSS) is an important standard device employed in measuring sound power. The specifications of RSS is specified in international standards, and it is classified as a major calibration item in the field of acoustic metrology. Since the output power of RSS is affected by the supply voltage, each country needs to secure its own calibration service system. In this study, a procedure for calibrating a RSS is established based on the reverberant room conditions and uncertainty evaluation is conducted. Basically, the calibration procedure can apply a precision measurement process of acoustic power, and here, the measurement method using the reverberation chamber of ISO 3741 is applied. For this purpose, a measurement system is constructed, measurements are conducted with two types of RSS, and measurement uncertainty is evaluated. Through measurement examples, it is confirmed that the non-uniformity of the sound pressure distribution in the reverberation room and the volume measurement uncertainty contributed significantly to the overall uncertainty. Additionally, the influence of input voltage is experimentally examined to examine the uncertainty contribution that can be reflected in acoustic power measurements.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2179-2183
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• 2009

As urbanization is progressed, the network for distributing water in a basin become complex due to the spatial expansion and parameter uncertainties of water supply systems. When a long range water supply plan is determined, the total construction and operation cost has to be evaluated with the system components and parameter uncertainties as many as possible. In this paper, the robust optimization approach of Bertsimas and Sim is applied in a hypothetical system to find a solution which remains feasible under the possible parameter uncertainties having the correlation effect between the uncertain coefficients. The system components to supply, treatment, and transport water are included in the developed water supply system and construction and expansion of the system is allowed for a long-range period. In this approach, the tradeoff between system robustness and total cost of the system is evaluated in terms of the degree of conservatism which can be converted to the probability of constraint violation. As a result, the degree of conservatism increases, the total cost is increased due to the installation of large capacity of treatment and transportation systems. The applied robust optimization technique can be used to determine a long-range water supply plan with the consideration of system failure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.26-32
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• 2010

This paper proposes a new effective installed reserve rate in order to evaluate reliability of power system considering renewable generators, which include uncertainty of resource supply. It is called EIRR(effective installed reserve rate) in this paper. It is developed with considering capacity credit based on ELCC by using LOLE reliability criterion. While the conventional installed reserve rate index yields over-evaluation reliability of renewable generators, the proposed EIRR describes actual effective installed reserve rate. However, it is not the probabilistic reliability index as like as LOLE or EENS but another deterministic effective reliability index. The proposed EIRR is able to evaluate the realistic contribution to the reliability level for power system considering wind turbine generators and solar cell generators with high uncertainty in resource supply. The case study in model system as like as Jeju power system size presents a possibility that the proposed EIRR can be used practically as a new deterministic reliability index for generation expansion planning or operational planning in future.

• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.231-249
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• 2014

This paper discusses a green supply chain with a manufacturer and a collection trader, and it proposes an optimal production planning for remanufacturing of parts in used products with quality classification errors made by the collection trader. When a manufacturer accepts an order for parts from a retailer and procures used products from a collection trader, the collection trader might have some quality classification errors due to the lack of equipment or expert knowledge regarding quality classification. After procurement of used products, the manufacturer inspects if there are any classification errors. If errors are detected, the manufacturer reclassifies the misclassified (overestimated) used products at a cost. Accordingly, the manufacturer decides to remanufacture from the higher-quality used products based on a remanufacturing ratio or produce parts from new materials. This paper develops a mathematical model to find how quality classification errors affect the optimal decisions for a lower limit of procurement quality of used products and a remanufacturing ratio under the lower limit and the expected profit of the manufacturer. Numerical analysis investigates how quality of used products, the reclassification cost and the remanufacturing cost of used products affect the optimal production planning and the expected profit of a manufacturer.

• Journal of the Korean Solar Energy Society
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• v.31 no.1
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• pp.51-58
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• 2011

The energy makes the basic element which improves the quality of life with motive power of industry and life. However, using the fossil fuel resources was restricted through it's abuse and exhaustion, and that cause a global warming resultingly. According to the reason, the world increased the interest that are stability and use of new and renewable energy which is clean energy with environment. Therefore, the property data of new and renewable is needed for developing and supplying the energy. In other words, the data of new and renewable energy becomes the standards for supply and evaluation of new and renewable energy with development of industry and technology. Also, the necessity came to the fore as the reference and standards of new and renewable energy data. Therefore, in this study, we evaluate and collect the solar radiation data as the new and renewable data and process the collected data through the standards for valuation. We evaluate uncertainty with standards which are NREL, WMO, and GUM. Whereby the data becomes reference standards data and gains the credibility. For the reliability data, we correct the measuring instrument with correction period. Using the DQMS and SERI QC, we efficiently manage and evaluate the solar radiation data. As a result, we evaluate uncertainty as 1,120 case about 16 area. we achieve credibility of data from evaluated solar radiation data and provide an accurate information to user. The annual average of horizontal radiation presents between 1,484 and 4,577, then the uncertainty evaluates from 163 to 453. The error of uncertainty presents smaller than the measurement values. So, we judge a credibility of data by expression of reliability quantitatively. In additional, the reference standards data which is possible to approach anywhere will be used for the supporting related industry and policy making.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.2
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• pp.183-188
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• 2014

In this paper, the propagation effect of power supply uncertainty on the output of class-F power amplifier has been estimated. Also, a 1.9 GHz, 10 watt class-F power amplifier was measured to verify the estimation and to find the optimal biasing point. By approximating the propagation theory of uncertainties, the propagation effect of bias uncertainty was mathmatically calculated. As a result, the DC biases have propagated uncertainties of 15~70 mW. However, at the optimized bias point, the uncertainty in the output power could be dropped less than 15 mW while the output power has dropped by 0.37 dB.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.44-51
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• 2017

In today's competitive environment, supply chain management is a major concern for a company. Two of the key issues in supply chain management are transportation and inventory management. To achieve significant savings, companies should integrate these two issues instead of treating them separately. In this paper we develop a framework for modeling stochastic programming in a supply chain that is subject to demand uncertainty. With reasonable assumptions, two stochastic programming models are presented, respectively, including a single-period and a multi-period situations. Our assumptions allow us to capture the stochastic nature of the problem and translate it into a deterministic model. And then, based on the genetic algorithm and stochastic simulation, a solution method is developed to solve the model. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

• Management Science and Financial Engineering
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• v.6 no.2
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• pp.1-28
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• 2000

Supply chain management issues faced by a manufacturing company are considered in this paper. The supply chain consists of a manufacturing company and its suppliers. The manufacturer produces multiple products with inputs (e.g., raw materials) from the suppliers, but each product needs a different mix of these inputs. The market demand for the products is uncertain. We develop a mathematical model and algorithm, which can help the manufacturer to solve its procurement decision problem: how much of raw material to order from which supplier. The model incorporates such factors as market demand uncertainty, product's input requirement, supplier's as well as manufacturer's capacity, plus other costs comparable with those in a typical newsboy problem. Numerical examples are presented to see the interacting effects among critical parameters and variables.