Displaying similar documents to “Efficient Improvement of Brain-Tharp's Algorithm”

Metaheuristics based on Bin Packing for the line balancing problem

Michel Gourgand, Nathalie Grangeon, Sylvie Norre (2007)

RAIRO - Operations Research

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The line balancing problem consits in assigning tasks to stations in order to respect precedence constraints and cycle time constraints. In this paper, the cycle time is fixed and the objective is to minimize the number of stations. We propose to use metaheuristics based on simulated annealing by exploiting the link between the line balancing problem and the bin packing problem. The principle of the method lies in the combination between a metaheuristic and a bin packing heuristic....

Tuning the Zhu-Takaoka string matching algorithm and experimental results

Thomas Berry, Somasundaram Ravindran (2002)

Kybernetika

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In this paper we present experimental results for string matching algorithms which have a competitive theoretical worst case run time complexity. Of these algorithms a few are already famous for their speed in practice, such as the Boyer–Moore and its derivatives. We chose to evaluate the algorithms by counting the number of comparisons made and by timing how long they took to complete a given search. Using the experimental results we were able to introduce a new string matching algorithm...

A modified K3M thinning algorithm

Marek Tabedzki, Khalid Saeed, Adam Szczepański (2016)

International Journal of Applied Mathematics and Computer Science

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The K3M thinning algorithm is a general method for image data reduction by skeletonization. It had proved its feasibility in most cases as a reliable and robust solution in typical applications of thinning, particularly in preprocessing for optical character recognition. However, the algorithm had still some weak points. Since then K3M has been revised, addressing the best known drawbacks. This paper presents a modified version of the algorithm. A comparison is made with the original...