Call for Papers on Advanced Optimization Methods for Uncertainties in Intelligent Industrial Systems
2021-09-13
With the rising complexity of problems, optimization has an inherent element of uncertainty that is expressed in many formal ways and this necessitates the need to develop novel techniques to create optimum and interpretable solutions for industrial operations. This special issue aims to discuss the intelligent optimization algorithms including particle swarm optimization, genetic algorithm, differential evolution, distribution estimation, ant colony optimization, artificial bee colony, greedy optimization, and many others, which have been successfully applied to different distributed scheduling problems as well as the real-time industrial systems.
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