Global minimization of a generalized linear multiplicative programming

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Abstract

This article presents a simplicial branch and bound algorithm for globally solving generalized linear multiplicative programming problem (GLMP). Since this problem does not seem to have been studied previously, the algorithm is apparently the first algorithm to be proposed for solving such problem. In this algorithm, a well known simplicial subdivision is used in the branching procedure and the bound estimation is performed by solving certain linear programs. Convergence of this algorithm is established, and some experiments are reported to show the feasibility of the proposed algorithm. © 2011 Elsevier Inc.

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Wang, C. F., Liu, S. Y., & Shen, P. P. (2012). Global minimization of a generalized linear multiplicative programming. Applied Mathematical Modelling, 36(6), 2446–2451. https://doi.org/10.1016/j.apm.2011.09.002

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