Abstract

We propose a general framework for modelling selection-and-scheduling problem with interdependencies in continuous time. Such problem may frequently arise in many real-world evaluation and decision-making contexts, such as project portfolio selection and scheduling in organisations, urban planning, and scheduling of public policies. For the purpose of conducting computational experiments, we further formulate a specific example model to optimise, whose benefit is to require a relatively limited number of input data. Given the NP-hardness of the problem, we employ the Covariance Matrix Adaptation Evolutionary strategy for solving it, and discuss few results.

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