An objective space cut and bound algorithm for convex multiplicative programmes

Lizhen Shao () and Matthias Ehrgott ()

Journal of Global Optimization, 2014, vol. 58, issue 4, 728 pages

Abstract: Multiplicative programming problems are global optimisation problems known to be NP-hard. In this paper we propose an objective space cut and bound algorithm for approximately solving convex multiplicative programming problems. This method is based on an objective space approximation algorithm for convex multi-objective programming problems. We show that this multi-objective optimisation algorithm can be changed into a cut and bound algorithm to solve convex multiplicative programming problems. We use an illustrative example to demonstrate the working of the algorithm. Computational experiments illustrate the superior performance of our algorithm compared to other methods from the literature. Copyright Springer Science+Business Media New York 2014

Keywords: Convex multiplicative programming; Convex multi-objective optimisation; Approximation algorithm; Nondominated point (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10898-013-0102-x

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