A hybrid evolutionary algorithm for multiobjective variation tolerant logic mapping on nanoscale crossbar architectures
The problem of variation tolerant logical mapping on nanoscale crossbar architectures is modeled as a bilevel multiobjective optimization problem. A hybrid multiobjective evolutionary algorithm is designed to solve the problem in a bilevel optimization framework. The lower level problem is modeled as a MMBM problem, and a Hungarian-based Linear Programming (HLP) method is proposed, which can solve MMBM in polynomial time. The upper level optimization problem is solved by evolutionary multiobjective optimization algorithms, where a greedy reassignment local search operator, capable of leveraging the domain knowledge and information from problem instances, is introduced to improve the efficiency of the algorithm.
hybrid evolutionary algorithm variation tolerant logic mapping nanoscale crossbar bilevel multiobjective optimization hungarian-based linear programming