Small and strong formulations for unions of convex sets from the Cayley embedding

成果类型:
Article
署名作者:
Vielma, Juan Pablo
署名单位:
Massachusetts Institute of Technology (MIT)
刊物名称:
MATHEMATICAL PROGRAMMING
ISSN/ISSBN:
0025-5610
DOI:
10.1007/s10107-018-1258-4
发表日期:
2019
页码:
21-53
关键词:
integer nonlinear programs
摘要:
There is often a significant trade-off between formulation strength and size in mixed integer programming. When modeling convex disjunctive constraints (e.g. unions of convex sets), adding auxiliary continuous variables can sometimes help resolve this trade-off. However, standard formulations that use such auxiliary continuous variables can have a worse-than-expected computational effectiveness, which is often attributed precisely to these auxiliary continuous variables. For this reason, there has been considerable interest in constructing strong formulations that do not use continuous auxiliary variables. We introduce a technique to construct formulations without these detrimental continuous auxiliary variables. To develop this technique we introduce a natural non-polyhedral generalization of the Cayley embedding of a family of polytopes and show it inherits many geometric properties of the original embedding. We then show how the associated formulation technique can be used to construct small and strong formulation for a wide range of disjunctive constraints. In particular, we show it can recover and generalize all known strong formulations without continuous auxiliary variables.