• Title/Summary/Keyword: Minimization

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Minimization Method for Solving a Quadratic Matrix Equation

  • Kim, Hyun-Min
    • Kyungpook Mathematical Journal
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    • v.47 no.2
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    • pp.239-251
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    • 2007
  • We show how the minimization can be used to solve the quadratic matrix equation and then compare two different types of conjugate gradient method which are Polak and Ribi$\acute{e}$re version and Fletcher and Reeves version. Finally, some results of the global and local convergence are shown.

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Determination of market share between railroad and road on the cost minimization base (비용최소화관점에서의 철도ㆍ도로 분담율에 관한 연구)

  • 이헌석;방연근;김경태
    • Proceedings of the KSR Conference
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    • 2000.11a
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    • pp.68-76
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    • 2000
  • Reliable external cost must be estimated to achieve the optimal market share between transportation modes. In this paper, we determined the market share between railroad and road on the cost minimization base. The results show that optimal market share is achieved by increasing investment on railroad.

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Minimization of Fuel Cost by Optimal Generation (연료비 최소화를 위한 유무효 발전력 분담)

  • 이상중
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2003.11a
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    • pp.289-290
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    • 2003
  • This paper gives a method for the minimization of the fuel cost by optimal generation. Derivation of the sensitivity of system loss by optimization technique is introduced and the loss sensitivities are substituted into the optimality conditions to obtain the minimized fuel cost.

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Determination of Cutting Direction for Tool Path Minimization in Zigzag Milling Operation (Zigzag 밀링가공에서 공구경로 최소화를 위한 가공방향 결정방법)

  • Kim, Byoung-Keuk;Park, Joon-Young
    • Journal of Korean Institute of Industrial Engineers
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    • v.27 no.1
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    • pp.69-88
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    • 2001
  • In the zigzag milling operation, an important issue is to design a machining strategy which minimizes the cutting time. An important variable for minimization of cutting time is the tool path length. The tool path is divided into cutting path and non-cutting path. Cutting path can be subdivided into tool path segment and step-over, and non-cutting path can be regarded as the tool retraction. We propose a new method to determine the cutting direction which minimizes the length of tool path in a convex or concave polygonal shape including islands. For the minimization of tool path length, we consider two factors such as step-over and tool retraction. Step-over is defined as the tool path length which is parallel to the boundary edges for machining area and the tool retraction is a non-cutting path for machining any remaining regions. In the determination of cutting direction, we propose a mathematical model and an algorithm which minimizes tool retraction length in complex shapes. With the proposed methods, we can generate a tool path for the minimization of cutting time in a convex or concave polygonal shapes including islands.

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An Algorithm for the Concave Minimization Problem under 0-1 Knapsack Constraint (0-1 배낭 제약식을 갖는 오목 함수 최소화 문제의 해법)

  • Oh, S.H.;Chung, S.J.
    • Journal of Korean Institute of Industrial Engineers
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    • v.19 no.2
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    • pp.3-13
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    • 1993
  • In this study, we develop a B & B type algorithm for the concave minimization problem with 0-1 knapsack constraint. Our algorithm reformulates the original problem into the singly linearly constrained concave minimization problem by relaxing 0-1 integer constraint in order to get a lower bound. But this relaxed problem is the concave minimization problem known as NP-hard. Thus the linear function that underestimates the concave objective function over the given domain set is introduced. The introduction of this function bears the following important meanings. Firstly, we can efficiently calculate the lower bound of the optimal object value using the conventional convex optimization methods. Secondly, the above linear function like the concave objective function generates the vertices of the relaxed solution set of the subproblem, which is used to update the upper bound. The fact that the linear underestimating function is uniquely determined over a given simplex enables us to fix underestimating function by considering the simplex containing the relaxed solution set. The initial containing simplex that is the intersection of the linear constraint and the nonnegative orthant is sequentially partitioned into the subsimplices which are related to subproblems.

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A New Algorithm for Boolean Function Minimization (부울함수의 간소화를 위한 새 방법)

  • 이우이
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.21 no.4
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    • pp.43-51
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    • 1984
  • In the case of Quine Mccluskey's methode for Boolean function minimization, we have to examine each bits of binary represented minterms. In this paper, cube relations between misterms that are represented by means of decimal number, and all sorts of rules for Boolean function minimization are described as theorems, and they are verified. And based on these theorems, the new fast algorithm for Boolean function minimization is proposed. An example of manual operation is sholvn, and the process is writed out by a FORTRAN program. In this program, the essential pl.imp implicants of the Boolean function that has 100 each of minterms including redundant minterms, are finked and printed out, (the more minterms can be treated if we take the more larger size of arrays) and the outputs are coincided with the results of manual operation.

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Reweighted L1-Minimization via Support Detection (Support 검출을 통한 reweighted L1-최소화 알고리즘)

  • Lee, Hyuk;Kwon, Seok-Beop;Shim, Byong-Hyo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.2
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    • pp.134-140
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    • 2011
  • Recent work in compressed sensing theory shows that $M{\times}N$ independent and identically distributed sensing matrix whose entries are drawn independently from certain probability distributions guarantee exact recovery of a sparse signal with high probability even if $M{\ll}N$. In particular, it is well understood that the $L_1$-minimization algorithm is able to recover sparse signals from incomplete measurements. In this paper, we propose a novel sparse signal reconstruction method that is based on the reweighted $L_1$-minimization via support detection.

Minimization of Losses in Permanent Magnet Synchronous Motors Using Neural Network

  • Eskander, Mona N.
    • Journal of Power Electronics
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    • v.2 no.3
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    • pp.220-229
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    • 2002
  • In this paper, maximum efficiency operation of two types of permanent magnet synchronous motor drives, namely; surface type permanent magnet synchronous machine (SPMSM) and interior type permanent magnet synchronous motor(IPMSM), are investigated. The efficiency of both drives is maximized by minimizing copper and iron losses. Loss minimization is implemented using flux weakening. A neural network controller (NNC) is designed for each drive, to achieve loss minimization at difffrent speeds and load torque values. Data for training the NNC are obtained through off-line simulations of SPMSM and IPMSM at difffrent operating conditions. Accuracy and fast response of each NNC is proved by applying sudden changes in speed and load and tracking the UC output. The drives'efHciency obtained by flux weakening is compared with the efficiency obtained when setting the d-axis current component to zero, while varying the angle of advance "$\vartheta$" of the PWM inverter supplying the PMSM drive. Equal efficiencies are obtained at diffErent values of $\vartheta$, derived to be function of speed and load torque. A NN is also designed, and trained to vary $\vartheta$ following the derived control law. The accuracy and fast response of the NN controller is also proved.so proved.

A Study on the Minimization of Fuzzy Rule Using Symbolic Multi-Valued Logic (기호다치논리를 이용한 Fuzzy Rule Minimization에 관한 연구)

  • 김명순
    • Journal of the Korea Society of Computer and Information
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    • v.4 no.4
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    • pp.1-8
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    • 1999
  • In the logic where we study the principle and method of human, the binary logic with the proposition which has one-valued property that it can be assigned the truth value 'truth'or 'false'. Although most of the traditional binary logic which was drawn by human includes fuzziness hard to deal with, the knowledge for expressing it is not precise and has less degree of credit. This study uses multi-valued logic in order to slove the problem above that .When compared with the data processing ability of the binary logic, Multi-valued logic has an at a high speed. Therefore the Inference can be possible by minimization multi-valued logic in stead of using the information stead of using the information system based on the symbolic binary logic.

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