Generic ILP versus specialized 0-1 ILP: an update
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Constraint integer programming: a new approach to integrate CP and MIP
CPAIOR'08 Proceedings of the 5th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Temperature- and energy-constrained scheduling in multitasking systems: a model checking approach
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Algebraic side-channel analysis in the presence of errors
CHES'10 Proceedings of the 12th international conference on Cryptographic hardware and embedded systems
Reconsidering mixed integer programming and MIP-Based hybrids for scheduling
CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Practical template-algebraic side channel attacks with extremely low data complexity
Proceedings of the 2nd International Workshop on Hardware and Architectural Support for Security and Privacy
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Pseudo-Boolean problems lie on the border between satisfiability problems, constraint programming, and integer programming. In particular, nonlinear constraints in pseudo-Boolean optimization can be handled by methods arising in these different fields: One can either linearize them and work on a linear programming relaxation or one can treat them directly by propagation. In this paper, we investigate the individual strengths of these approaches and compare their computational performance. Furthermore, we integrate these techniques into a branch-and-cut-and-propagate framework, resulting in an efficient nonlinear pseudo-Boolean solver.