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This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be(More)
This paper presents an effective and efficient method for speeding up ant colony optimization (ACO) in solving the codebook generation problem. The proposed method is inspired by the fact that many computations during the convergence process of ant-based algorithms are essentially redundant and thus can be eliminated to boost their convergence speed,(More)
This paper presents an efficient algorithm for reducing the computation time of metaheuristics. The proposed algorithm is motivated by the observation that some of the subsolutions of metaheuristics will eventually end up being part of the final solutions. As such, if they can be saved away as soon as they were found, then most, if not all, of the redundant(More)
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(More)
Harmony search (HS) is a promising metaheuristic algorithm inspired by music improvisation process for various hard optimization problems. HS has attracted attention of researchers from different areas because it is easy to implement and can be applied to different optimization problems. in this paper, we present a novel method to improve the result of HS(More)