An improved linearization technique for a class of quadratic 0-1 programming problems

The recent research on linearization techniques for solving 0-1 quadratic programming problems focuses on providing concise models and tightening constraint bounds. In this paper, we propose a computational enhancement for a linearization technique to make the linearized model much faster to solve....

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Bibliographic Details
Published in:Optimization letters Vol. 6; no. 1; pp. 31 - 41
Main Authors: He, Xiaozheng, Chen, Anthony, Chaovalitwongse, Wanpracha A., Liu, Henry X.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer-Verlag 01.01.2012
Subjects:
Computational Intelligence
Mathematics
Mathematics and Statistics
Numerical and Computational Physics
Operations Research/Decision Theory
Optimization
Original Paper
Simulation
Linearization technique
Binary quadratic programming problem
Hub location problem
ISSN:1862-4472, 1862-4480
Online Access:Get full text
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Summary:The recent research on linearization techniques for solving 0-1 quadratic programming problems focuses on providing concise models and tightening constraint bounds. In this paper, we propose a computational enhancement for a linearization technique to make the linearized model much faster to solve. We investigate the computational performance of the proposed approach, by comparing it with other linearization techniques on a class of 0-1 quadratic programming problems. We can further speed up the proposed technique by heuristically tightening the constraint bounds, as demonstrated by solving the uncapacitated single allocation p -hub median problem using the Civil Aeronautics Board data.
ISSN:1862-4472
1862-4480
DOI:10.1007/s11590-010-0249-z