期刊
COMPUTERS & CHEMICAL ENGINEERING
卷 34, 期 12, 页码 2097-2106出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2010.07.032
关键词
Integer and mixed-integer bilevel programming; Multiparametric programming; Global optimization; Reformulation linearization technique
资金
- Mexican Council for Science and Technology (CONACyT)
- European Research Council [226462]
- EPRSC [EP/G059071/1]
- KAUST
- CPSE Industrial Consortium
- EPSRC [EP/E047017/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/E047017/1] Funding Source: researchfish
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. (C) 2010 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据