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    Multiparametric programming based algorithms for pure integer and mixed-integer bilevel programming problems

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    Type
    Article
    Authors
    Domínguez, Luis F.
    Pistikopoulos, Efstratios N.
    Date
    2010-12
    Permanent link to this record
    http://hdl.handle.net/10754/598906
    
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    Abstract
    This work introduces two algorithms for the solution of pure integer and mixed-integer bilevel programming problems by multiparametric programming techniques. The first algorithm addresses the integer case of the bilevel programming problem where integer variables of the outer optimization problem appear in linear or polynomial form in the inner problem. The algorithm employs global optimization techniques to convexify nonlinear terms generated by a reformulation linearization technique (RLT). A continuous multiparametric programming algorithm is then used to solve the reformulated convex inner problem. The second algorithm addresses the mixed-integer case of the bilevel programming problem where integer and continuous variables of the outer problem appear in linear or polynomial forms in the inner problem. The algorithm relies on the use of global multiparametric mixed-integer programming techniques at the inner optimization level. In both algorithms, the multiparametric solutions obtained are embedded in the outer problem to form a set of single-level (M)(I)(N)LP problems - which are then solved to global optimality using standard fixed-point (global) optimization methods. Numerical examples drawn from the open literature are presented to illustrate the proposed algorithms. © 2010 Elsevier Ltd.
    Citation
    Domínguez LF, Pistikopoulos EN (2010) Multiparametric programming based algorithms for pure integer and mixed-integer bilevel programming problems. Computers & Chemical Engineering 34: 2097–2106. Available: http://dx.doi.org/10.1016/j.compchemeng.2010.07.032.
    Sponsors
    The authors gratefully acknowledge the financial support from the Mexican Council for Science and Technology (CONACyT), the European Research Council (MOBILE, ERC Advanced Grant, No: 226462), EPRSC (Grant EP/G059071/1), KAUST and the CPSE Industrial Consortium.
    Publisher
    Elsevier BV
    Journal
    Computers & Chemical Engineering
    DOI
    10.1016/j.compchemeng.2010.07.032
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.compchemeng.2010.07.032
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