Theory of linear and integer programming
Theory of linear and integer programming
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Channel density reduction by routing over the cells
DAC '91 Proceedings of the 28th ACM/IEEE Design Automation Conference
Engineering change in a non-deterministic FSM setting
DAC '96 Proceedings of the 33rd annual Design Automation Conference
Engineering change: methodology and applications to behavioral and system synthesis
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Incremental logic synthesis through gate logic structure identification
DAC '86 Proceedings of the 23rd ACM/IEEE Design Automation Conference
Boolean satisfiability in electronic design automation
Proceedings of the 37th Annual Design Automation Conference
Logic synthesis for engineering change
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Engineering change using spare cells with constant insertion
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Spare cells with constant insertion for engineering change
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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We have developed a generic integer linear programming(ILP)-based engineering change(EC) methodology. The EC methodology has three components: enabling, fast, and preserving. Enabling EC provides a user with the means to specify the amount of flexibility and how this flexibility should be distributed throughout the solution so that one can guarantee that a specific set of EC demands can be satisfied while preserving the quality of the initially obtained solution. Fast EC conducts changes in a fraction of the time needed to solve the problem while preserving or in some cases improving the quality of the initial solution. Preserving EC maintains either user specified components of the solution or as much as possible of the initial solution while still guaranteeing an optimal solution to the altered problem instance. We applied the generic methodology to Boolean Satisfiability (SAT) problem. The effectiveness of all proposed approaches and algorithms is demonstrated on standard benchmarks.