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The class of continuous time Bayesian network classifiers is defined; it solves the problem of supervised classification on multivariate trajectories evolving in continuous time. The trajectory consists of the values of discrete attributes that are measured in continuous time, while the predicted class is expected to occur in the future. Two instances from(More)
Supply chain management aims to add value across the supply chain and customer service is now a major strategic issue. Supply chains are complex and subject to variables of forecast, supply, process, and transportation which can lead to problems such as the bull whip effect, product lateness, damaged goods and stock outs. A key issue facing companies today(More)
This paper presents a survey on studies devising biased-random key genetic algorithms (BRKGAs), a novel variant of the ordinary genetic algorithms (GAs) introduced in 2000s, for solving numerous optimization problems up to 2015. The aim is to provide a comprehensive picture of the development of the algorithms and the areas of implementation in literature(More)
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