A Framework for Accelerating Metaheuristics via Pattern Reduction

摘要

This paper presents a novel framework based on the notion of pattern reduction, called Framework for Accelerating Metaheuristics via Pattern Reduction (FAMPR), to solve an intrinsic problem of metaheuristics. That is, many computations of metaheuristics during the convergence process are essentially redundant. As such, if they can be eliminated, the computation time of metaheuristics can be significantly reduced. Our experimental result shows that the proposed framework can significantly reduce the computation time of metaheuristics while limiting the loss of quality to a very small percentage.