Bilevel programming applied to the flow shop scheduling problem
Computers and Operations Research
A bilevel model of taxation and its application to optimal highway pricing
Management Science
Constraint-Based Scheduling
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Solving quantified constraint satisfaction problems
Artificial Intelligence
Modeling adversary scheduling with QCSP+
Proceedings of the 2008 ACM symposium on Applied computing
Quantified Constraint Optimization
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Toll Policies for Mitigating Hazardous Materials Transport Risk
Transportation Science
QCSP made practical by virtue of restricted quantification
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
QCSP-solve: a solver for quantified constraint satisfaction problems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
BlockSolve: a bottom-up approach for solving quantified CSPs
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
On bilevel machine scheduling problems
OR Spectrum
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Bilevel optimization problems involve two decision makers who make their choices sequentially, either one according to its own objective function. Many problems arising in economy and management science can be modeled as bilevel optimization problems. Several special cases of bilevel problem have been studied in the literature, e.g., linear bilevel problems. However, up to now, very little is known about solution techniques of discrete bilevel problems. In this paper we show that constraint programming can be used to model and solve such problems. We demonstrate our first results on a simple bilevel scheduling problem.