• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.21-25
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• 1999

Planning support systems(PSS) add more advanced spatial analysis functions than Geographic information systems(GIS) and intertemporal functions to the functions of spatial decision support systems(SDSS). This paper reports the continuing development of a PSS providing a framework that facilitates urban planners and civil engineers in conducting coherent deliberations about planning, design and operation & maintenance(O&M) of water-distribution networks for urban growth management. The PSS using dynamic optimization model, modeling-to-generate-alternatives, value engineering(VE) and life-cycle cost(LCC) can generate network alternatives in consideration of initial cost and O&H cost. Users can define alternatives by the direct manipulation of networks or by the manipulation of parameters in the models. The water-distribution network analysis model evaluates the performance of the user-defined alternatives. The PSS can be extended to include the functions of generating sewer network alternatives, combining water-distribution and sewer networks, eventually the function of planning, design and O&H of housing sites. Capacity expansion by the dynamic water-distribution network optimization model using MINLP includes three advantages over capacity expansion using optimal control theory(Kim and Hopkins 1996): 1) finds expansion alternatives including future capacity expansion times, sizes, locations, and pipe types of a water-distribution network provided, 2) has the capabilities to do the capacity expansion of each link spatially and intertemporally, and 3) requires less interaction between models. The modeling using MINLP is limited in addressing the relationship between cost, price, and demand, which the optimal control approach can consider. Strictly speaking, the construction and O&M costs of water-distribution networks influence the price charged for the served water, which in turn influence the. This limitation can be justified in rather small area because price per unit water in the area must be same as that of neighboring area, i.e., the price is determined administratively. Planners and engineers can put emphasis on capacity expansion without consideration of the relationship between cost, price, and demand.

• Journal of Internet Computing and Services
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• v.5 no.5
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• pp.17-26
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• 2004

Mobile multicast schemes are classified into remote subscription and bi-directional tunneling. While the former scheme has much overhead in the maintenances of multicast tree, the latter suffers from inefficient routing. In this paper, we propose dynamic mobile multicast routing (DMMR) scheme, which is operated on the basis of cost functions related with forwarding cost and tree reconstruction cost, Basically DMMR intends to find lower cost between forwarding cost and tree reconstruction cost. Forwarding cost is the cost of tunneling multicast packets from home agent, and tree reconstruction cost is the joining cost of foreign agent to multicast group. In the case that a mobile host moves to the other area, its foreign agent calculates cost functions related with forwarding cost and tree reconstruction cost. If forwarding cost is higher than tree reconstruction cost, foreign agent joins to multicast group and reconstructs the multicast tree. Accordingly, foreign agent can dynamically adapt remote subscription or bi-directional tunneling, Our scheme provides more stable multicast service to the mobile hosts regardless of the movements of mobile host and the number of mobile group members.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.848-853
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• 2007

This paper presents a methodology of estimating incomplete information in electricity markets for analyzing the gaming behavior of Generating Companies (GENCOs). Each GENCO needs to model its opponents' unknown information of strategic biddings and cost functions. In electricity markets with complete information, each GENCO knows its rivals' payoff functions and tries to maximize its own profit at Nash equilibriurnl Nli) by acknowledging the rivals' cost function. On the other hand, in the incomplete information markets, each GENCO lacks information about its rivals. Load patterns can change continuously due to many factors such as weather, price, contingency, etc. In this paper, we propose the method of the estimation of the opponents' cost function using market price, transaction quantities. and customer load patterns. A numerical example with two GENCOs is illustrated to show the basic idea and effectiveness of the proposed methodology.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.6-14
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• 2012

All types of part-of-speech (POS) tagging errors have been equally treated by existing taggers. However, the errors are not equally important, since some errors affect the performance of subsequent natural language processing seriously while others do not. This paper aims to minimize these serious errors while retaining the overall performance of POS tagging. Two gradient loss functions are proposed to reflect the different types of errors. They are designed to assign a larger cost for serious errors and a smaller cost for minor errors. Through a series of experiments, it is shown that the classifier trained with the proposed loss functions not only reduces serious errors but also achieves slightly higher accuracy than ordinary classifiers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.5 no.6
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• pp.69-78
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• 1982

Traditional CVP (Cost-Volume-Profit) analysis employs linear cost and revenue functions within some specified time period and range of operations. Therefore CVP analysis is assumption of constant labor productivity. The use of linear cost functions implicity assumes, among other things, that firm's labor force is either a homogenous group or a collection homogenous subgroups in a constant mix, and that total production changes in a linear fashion through appropriate increase or decrease of seemingly interchangeable labor unit. But productivity rates in many firms are known to change with additional manufacturing experience in employee skill. Learning curve is intended to subsume the effects of all these resources of productivity. This learning phenomenon is quantifiable in the form of a learning curve, or manufacturing progress function. The purpose d this study is to show how alternative assumptions regarding a firm's labor force may be utilize by integrating conventional CVP analysis with learning curve theory, Explicit consideration of the effect of learning should substantially enrich CVP analysis and improve its use as a tool for planning and control of industry.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.12-14
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• 1994

Traditionally one convex cost function for each generation is assumed in economic power dispatch. However, it is more realistic to represent the cost function as a piecewise quadratic function rather than one convex function. This paper presents evolutionary algorithm approaches to solve the problems of economic power dispatch with quadratic cost functions and piecewise quadratic cost functions. To improve GA, EP and ES characteristics. optimization methods combining GA with ES and EP with ES are proposed. The results for the proposed algorithms are compared with those of numerical method and show the better solutions in the ELD problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.233-240
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• 1996

A fixed amount compensator is proposed for a process with a linear tool wear function. A Cost model is constructed which involve process adjustment cost and quality loss. Symmetric and asymmetric quadratic functions of the deviation of a quality measurement from the nominal target value are considered as the quality loss functions. Methods of finding optimal values of initial setting and compensation limit are presented and a numerical example is given.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.143-146
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• 2004

This paper presents a method to improve reliability by dispersed generation (DG) installation considering load types and interruption cost. The objective functions such as power losses cost, operation cost of DGS, power buy cost and interruption cost are minimized for reliability improvement and efficient operation. The several indices for reliability evaluation are improved by dispersed generation system installation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.257-266
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• 2015

There is no polynomial-time algorithm that can be obtain the optimal solution for economic load dispatch problem with non-convex fuel cost functions. Therefore, electrical field uses quadratic fuel cost function unavoidably. This paper proposes a valve-point optimization (VPO) algorithm for economic load dispatch problem with non-convex fuel cost functions. This algorithm sets the initial values to maximum powers $P_i{\leftarrow}P_i^{max}$ for each generator. It then reduces the generation power of generator i with an average power cost of $_{max}\bar{c}_i$ to a valve point power $P_{ik}$. The proposed algorithm has been found to perform better than the extant heuristic methods when applied to 13 and 40-generator benchmark data. This paper consequently proves that the optimal solution to economic load dispatch problem with non-convex fuel cost functions converges to the valve-point power of each generator.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.1
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• pp.3-10
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• 1985

Periodic replacement policies are proposed for a system whose repair cost, when it fails, can be estimated by inspection. The system is replaced when it reaches age T (Policy A), or when it fails for the first time after age T (Policy B). If it fails before reaching age T, the repair cost is estimated and minimal repair is then undertaken if the estimated cost is less than a predetermined limit L; otherwise, the system is replaced. The expected cost rate functions are obtained, their behaviors are examined, and ways of obtaining optimal T and L are explored.