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Author: search.filters.author.Li, HLSubject: search.filters.subject.optimization

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Now showing 1 - 4 of 4
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    Item type:Item,
    An approximately global optimization method for assortment problems
    (1998-03-16)
    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
    Assortment problems occur when we want to cut a number of small rectangular pieces from a large rectangle to get the minimum area within the rectangle. Recently, Chen et al. proposed a useful model for assortment problems. Although Chen et al.'s model is quite promising to find solutions, there are two inadequacies in their model: firstly, the objective function in their model is a polynomial term, which may not lead to a globally optimal solution; secondly, too many 0-1 variables are used to formulate the non-overlapping constraints. We propose a new method to reformulate an assortment model. Our model is not only able to find the approximately global optimal solution, but involves less 0-1 variables for formulating non-overlapping constraints. (C) 1998 Elsvier Science B.V.
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    Item type:Item,
    A fast algorithm for assortment optimization problems
    (2001-10-01)
    Li, HL
    ;
    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
    Assortment optimization problems intend to seek the best way of placing a given set of rectangles within a minimum-area rectangle. Such problems are often formulated as a quadratic mixed 0-1 program. Many current methods for assortment problems are either unable to find an optimal solution or being computationally inefficient for reaching an optimal solution. This paper proposes a new method which finds the optimum of assortment problem by solving few linear mixed 0-1 programs. Numerical examples show that the proposed method is more computationally efficient than current methods.
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    Item type:Item,
    A distributed global optimization method for packing problems
    (2003-04-01)
    Li, HL
    ;
    Tsai, JF
    ;
    Hu, NZ
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    Packing optimization problems aim to seek the best way of placing a given set of rectangular cartons within a minimum volume rectangular container. Currently, packing optimization methods either have difficulty in finding a globally optimal solution or are computationally inefficient, because models involve too many 0-1 variables and because use of just a single computer. This study proposes a distributed computation method for solving a packing problem by a set of personal computers via the Internet. First, the traditional packing optimization model is converted into an equivalent model containing many fewer 0-1 variables. Then the model is decomposed into several sub-problems by dividing the objective value into many intervals. Each of these sub-problems is a linearized logarithmic program expressed as a linear mixed 0-1 problem. The whole problem is solvable and reaches a globally optimal solution. The numerical examples demonstrate that the proposed method can obtain the global optimum of a packing problem effectively.
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    Constrained abductive reasoning with fuzzy parameters in Bayesian networks
    (2005-01-01)
    Li, HL
    ;
    Kao, HY
    ;
    資訊管理與財務金融系 註：原資管所+財金所
    ;
    Department of Information Management and Finance
    This work proposes a novel approach for solving abductive reasoning problems in Bayesian networks involving fuzzy parameters and extra constraints. The proposed method formulates abduction problems using nonlinear programming. To maximize the sum of the fuzzy membership functions subjected to various constraints, such as boundary, dependency and disjunctive conditions, unknown node belief propagation is completed. The model developed here can be built on any exact propagation methods, including clustering, joint tree decomposition, etc. (C) 2003 Elsevier Ltd. All rights reserved.