A Tight Linearization Strategy for Zero-One Quadratic Programming Problems

Details A Tight Linearization Strategy for Zero-One Quadratic Programming Problems A Tight Linearization Strategy for Zero-One Quadratic Programming Problems

2012-04-20

arxiv.org/abs/1204.4562v1

International Journal of Computer Science Issues, IJCSI Volume 9, Issue 2, March 2012

Computer Science

Data Structures and Algorithms

6 pages

Scientific paper

In this paper, we present a new approach to linearizing zero-one quadratic minimization problem which has many applications in computer science and communications. Our algorithm is based on the observation that the quadratic term of zero-one variables has two equivalent piece-wise formulations, convex and concave cases. The convex piece-wise objective function and/or constraints play a great role in deducing small linearization. Further tight strategies are also discussed.

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