Journal of the ACM (JACM)
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
A machine program for theorem-proving
Communications of the ACM
Solving difficult SAT instances in the presence of symmetry
Proceedings of the 39th annual Design Automation Conference
A Decoder-Based Evolutionary Algorithm for Constrained Parameter Optimization Problems
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Generic ILP versus specialized 0-1 ILP: an update
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
A fast pseudo-boolean constraint solver
Proceedings of the 40th annual Design Automation Conference
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Efficient symbolic multi-objective design space exploration
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
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This paper presents a feasibility-preserving crossover and mutation operator for evolutionary algorithms for constrained combinatorial problems. This novel operator is driven by an adapted Pseudo-Boolean solver that guarantees feasible offspring solutions. Hence, this allows the evolutionary algorithm to focus on the optimization of the objectives instead of searching for feasible solutions. Based on a proposed scalable testsuite, six specific testcases are introduced that allow a sound comparison of the feasibility-preserving operator to known methods. The experimental results show that the introduced approach is superior to common methods and competitive to a recent state-of-the-art decoding technique.