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In this paper we propose a novel method to improve seam carving based on the method meta-heuristic algorithms combining simulated annealing (SA) and genetic algorithm (GA). SA is a single solution method which searches locally while GA belongs to population based algorithms that globally search to find the best answer. By this strategy, both speed and quality of the seam carving method can be increased...
In this paper, the multi-mode resource-constrained project scheduling problem (MRCPSP) is considered. The MRCPSP is extremely complex and is known to be NP-hard problem. In order to obtain satisfactory sub optimal solutions within a reasonable amount of computational time, various met heuristic techniques have been developed to solve MRCPSP. For a metaheuristic algorithm, too much emphasis on the...
Feature selection is to select an informative subset from original feature set aiming at reducing the dimension of the feature space and enhancing the performance of the classifier. It is a crucial problem of pattern recognition and has attracted much attention in recent years. In this paper, we have proposed a multi-population univariate marginal distribution algorithm using random population to...
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