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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Chang, CTSubject: search.filters.subject.global optimization

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    Item type:Item,
    An approximate approach of global optimization for polynomial programming problems
    (1998-06-16)
    Li, HL
    ;
    Chang, CT
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    Many methods for solving polynomial programming problems can only find locally optimal solutions. This paper proposes a method for finding the approximately globally optimal solutions of polynomial programs. Representing a bounded continuous variable x(i) as the addition of a discrete variable d(i) and a small variable epsilon(i), a polynomial term x(i)x(j) can be expanded as the sum of d(i)x(j), d(j) epsilon(i) and epsilon(i) epsilon(j). A procedure is then developed to fully linearize d(i)x(j) and d(j) epsilon(i), and to approximately linearize epsilon(i) epsilon(j) with an error below a pre-specified tolerance. This linearization procedure can also be extended to higher order polynomial programs. Several polynomial programming examples in the literature are tested to demonstrate that the proposed method can systematically solve these examples to find the global optimum within a pre-specified error. (C) 1998 Elsevier Science B.V.
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    Item type:Item,
    Approximately global optimization for assortment problems using piecewise linearization techniques
    (2002-08-01)
    Li, HL
    ;
    Chang, CT
    ;
    Tsai, JF
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    Recently, Li and Chang proposed an approximate model for assortment problems. Although their model is quite promising to find approximately global solution, too many 0-1 variables are required in their solution process. This paper proposes another way for solving the same problem. The proposed method uses iteratively a technique of piecewise linearization of the quadratic objective function. Numerical examples demonstrate that the proposed method is computationally more efficient than the Li and Chang method. (C) 2002 Elsevier Science B.V. All rights reserved.