Who are the variables in your neighborhood
ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
Improving the Variable Ordering of OBDDs Is NP-Complete
IEEE Transactions on Computers
Fast exact minimization of BDDs
DAC '98 Proceedings of the 35th annual Design Automation Conference
Quantum computation and quantum information
Quantum computation and quantum information
Speeding up variable reordering of OBDDs
ICCD '97 Proceedings of the 1997 International Conference on Computer Design (ICCD '97)
BDD Variable Ordering by Scatter Search
ICCD '01 Proceedings of the International Conference on Computer Design: VLSI in Computers & Processors
A New Quantum Evolutionary Local Search Algorithm for MAX 3-SAT Problem
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
IEEE Transactions on Evolutionary Computation
A novel quantum inspired cuckoo search for knapsack problems
International Journal of Bio-Inspired Computation
A hybrid quantum inspired harmony search algorithm for 0-1 optimization problems
Journal of Computational and Applied Mathematics
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In this work, the authors focus on the quantum evolutionary quantum hybridization and its contribution in solving the binary decision diagram ordering problem. Therefore, a problem formulation in terms of quantum representation and evolutionary dynamic borrowing quantum operators are defined. The sifting search strategy is used in order to increase the efficiency of the exploration process, while experiments on a wide range of data sets show the effectiveness of the proposed framework and its ability to achieve good quality solutions. The proposed approach is distinguished by a reduced population size and a reasonable number of iterations to find the best order, thanks to the principles of quantum computing and to the sifting strategy.