• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.573-580
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• 2004

A new real-time constrained dispatch scheduling (CDS) is needed for TWBP. The CDS needs to be performed at every dispatch period to decide generation power of scheduling generators and amounts of scheduling load. Therefore, the CDS is not based on real generation costs but on bidding data of market participants with some constraints such as power balance, generation limits, ancillary service, and transmission line limits. This paper selects linear programming(LP) as an optimization tool for the CDS and presents effective formulae for the LP application. This paper also presents the way of minimizing the number of variables and constraints of the LP to improve real-time applicability.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.273-282
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• 2002

Although the influence of GIS has been proved in a variety of applications, there also have been some research issues about that the coupling of GIS with other mathematical or engineering tools is necessary to meet various needs of specialized problem domains. Linear Programming, a mathematical technique used in optimal distribution of given quantity, can enhance its usability by integrating with GIS since LP basically does not include means to deal with spatial data. The limitation of the traditional LP technique is that it requires explicitly defined conditions, which is impractical or impossible in such decision making processes as in land use problems that use less crisp decision factors. This study develops a method to incorporate such fuzzy situations by integrating Fuzzy-LP that employs fuzzy logic and GIS. The GIS provides data to or displays data from the Fuzzy-LP processes in the integrated system. This methodology is illustrated to solve a land use distribution problem.

• Management Science and Financial Engineering
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• v.9 no.2
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• pp.13-20
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• 2003

For inferring criteria in a performance appraisal. linear programming (LP) has been utilized as an alternative to policy capturing (PC). Previous policy capturing LP (PCLP) studies were limited to the criteria of exact numerical ratings. However. under certain evaluation circumstances, a ranged rating with a lower and upper bound may be preferred over an exact numerical value. Therefore, this study introduces a new LP model that allows ranged ratings. A simple example is given to illustrate our model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.203-217
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• 1996

This thesis describes a quantitative decision-making of production planning system. A mathmatical model of Linear Programming is used set up a production scheuling under the assumption. As the emphasis is laid on the applicability of the developed model, the linrar programming is applied to establish the production schedule for "F" furniture company which produces kitchin cabinet and OA furniture, The optimal solution is obtained by using the LP package, QBS. By the solution reduced to 14% of work force compared with the real data during all of the planning horizon. And it is also possible to reduce the work-force of the lowest level of employee by 10% for the reasonable management. There are some limitations in computerized data processing, which is only considering the economic costs without considering any external environment of case enterprise. As a result, it is shown that the LP model is very useful method of make aggregate production schedule. schedule.

• Journal of Educational Research in Mathematics
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• v.20 no.1
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• pp.85-102
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• 2010

Linear programming(LP) is useful for finding the best way in a given condition for some list of requirements represented as linear equations. This study analysed LP in mathematics contexts and LP in school mathematics contexts, considered learning process of LP from an epistemological point of view, and explored a hypothetical learning trajectory of LP. The differences between mathematics contexts and school mathematics contexts are whether they considered that the convex polytope $\Omega$ is feasible/infeasible or bounded/unbounded or not, and whether they prove the theorem that the optimum is always attained at a vertex of the polyhedronor not. And there is a possibility that students could not understand what is maximum and minimum of a linear function when the domain of the function is limited. By considering these three aspects, we constructed hypothetical learning trajectory consisted of 4 steps. The first step is to see a given linear expression as linear function, the second step is to partition a given domain by straight lines, the third step is to construct the conception of y-intercept by relating lines and the range of k, and the forth step is to identify whether there exists the optimum in a given domain or not.

• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.145-148
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• 2000

This paper presents new algorithm which is based on LP(Linear Programming) that guarantee convergence. It is considered to minimize generation cost and load shedding as object function subject to various constraints. The proposed algorithm use sensitivity matrix to re-dispatch generation power, so the total CPU time is saved.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.274-280
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• 2001

In this research, we develop a specialized primal-dual interior point solver for the multicommodity flow problems (MCFP). The Castro's approach that exploits the problem structure is investigated and several aspects that must be considered in the implementation are addressed. First, we show how preprocessing techniques for linear programming(LP) are adjusted for MCFP. Secondly, we develop a procedure that extracts a network structure from the general LP formulated MCFP. Finally, we consider how the special structure of the mutual capacity constraints is exploited. Results of comupational comparison between our solver and a general interior point solver are also included.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.200-202
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• 1999

This paper describes the optimization problem of real power rescheduling and present an algorithm based linear programming for studying the load-shedding and generation reallocation problem when a portion of the transmission system is disabled and at power flow solution cannot be obtained for the overload of some lines. And in case initial is infeasible, solution could not be converge. So this paper gives an algorithm being lie infeasible quantities within limit. The paper describes a LP-based algorithm to obtain the solution in power dispatch related to overload situations in power system and it is easily extened under various objective. The optimization procedures is based in linear programming with bounded variables and use the multi-segment curve method for a objective function and the validity of the algorithm is verified with two examples : 10-bus system and 57-bus system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.255-260
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• 2017

This paper studies on effective rescheduling of generation when the single line contingency has occurred in power system with wind farm. The suggested method is formulated to minimize the rescheduling cost of conventional and wind generators to alleviate congestion. The generator rescheduling method has been used with incorporation of wind farms in the power system. Since all sensitivity is different about congestion line, Line Outage Distribution Factor(LODF) and Generator Sensitivity Factor(GSF) is used to alleviate congestion. The formulation have been proccessed using linear programming(LP) optimization techniques to alleviate transmission congestion. The effectiveness of the proposed rescheduling of generation method has been analyzed on revised IEEE 30-bus systems.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.396-403
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• 2014

The multi-divisional knapsack problem is defined as a binary knapsack problem where each mutually exclusive division has its own capacity. In this paper, we present an extension of the multi-divisional knapsack problem that has generalized multiple-choice constraints. We explore the linear programming relaxation (P) of this extended problem and identify some properties of problem (P). Then, we develop a transformation which converts the problem (P) into an LP knapsack problem and derive the optimal solutions of problem (P) from those of the converted LP knapsack problem. The solution procedures have a worst case computational complexity of order $O(n^2{\log}\;n)$, where n is the total number of variables. We illustrate a numerical example and discuss some variations of problem (P).