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.
Original language | English |
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Pages (from-to) | 922-934 |
Number of pages | 13 |
Journal | European Journal of Operational Research |
Volume | 255 |
Issue number | 3 |
DOIs | |
State | Published - 1 Dec 2016 |
Keywords
- Linearization technique
- Mixed 0-1 linear programming
- Signomial programming