Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4959824 | European Journal of Operational Research | 2016 | 13 Pages |
Abstract
Signomial programming problems with discrete variables (SPD) appear widely in real-life applications, but they are hard to solve. This paper proposes an enhanced logarithmic method to reformulate the SPD problem as a mixed 0-1 linear program (MILP) with a minimum number of binary variables and inequality constraints. Both of the theoretical analysis and numerical results strongly support its superior performance to other state-of-the-art linearization methods. We also extend the proposed method to linearize some more complicated problems involving product and fractional terms in discrete and continuous variables.
Keywords
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Han-Lin Li, Shu-Cherng Fang, Yao-Huei Huang, Tiantian Nie,