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In this work, we propose a stochastic level-set method to reconstruct binary tomography cross-sections from few projections. A first reconstruction image is obtained with a level-set regularization method. The reconstruction is then refined with a stochastic partial differential equation based on a Stratanovitch formulation. The reconstruction results are compared with the ones obtained with the classical...
Wind energy is becoming an important renewable resource for a residence with no access to grid-based power. However, its variable and uncertain nature requires the use of energy storage to ensure high reliability of power to the residential loads. Therefore, variations in the wind profile need to be considered more accurately to predict energy storage requirements. Various models aim to develop simulated...
In typical production scheduling problems, flow shop scheduling is one of the strongly NP-complete combinatorial optimisation problems with a strong engineering background. In this paper, after investigating the effect of different initialisation, crossover and mutation operators on the performances of a genetic algorithm (GA), we propose an effective hybrid heuristic for flow shop scheduling. First,...
As a class of typical production scheduling problems, job shop scheduling is one of the strongly NP-complete combinatorial optimisation problems, for which an enhanced genetic algorithm is proposed in this paper. An effective crossover operation for operation-based representation is used to guarantee the feasibility of the solutions, which are decoded into active schedules during the search process...
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