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This study theorizes how the optimal control paradigm can be applied to modeling and algorithmic solutions in manufacturing systems with dynamically changing hybrid structural-logical-terminal constraints. Our study conceptualizes and operationalizes a unique class of problems with both flexible machines and flexible jobs that can be frequently encountered in manufacturing systems with individualized products when process and schedule are created simultaneously. We offer a model to schedule jobs in manufacturing systems when the structural-logical terminal constraints are changing dynamically, and an algorithm to obtain a tractable solution analytically within the proven axiomatic of the optimal program control and mathematical optimization. We develop a dynamic decomposition methodology for modeling and control of schedules in highly flexible production systems combining the advantages of continuous and discrete optimization. The findings suggest that our approach can be of value for approaching problems with a simultaneous process design (i.e., task composition) and operation sequencing (i.e., service composition). Utilizing the outcomes of this research could also support the consideration of dynamics in the operations control. The operations execution can be accurately modeled in continuous time as state variables the updates of which allow for data-driven control of machine availability and capacity disturbances. Besides, the method developed theorizes further generalized insights into decomposition methods for scheduling and is supported by an analytical analysis and an algorithmic realization.

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In this paper a new approach to the creation of short-term forecasting systems of river flooding is being further developed. It provides highly accurate forecasting results due to operative obtaining and integrated processing of the remote sensing and ground-based water flow data in real time. Forecasting of flood areas and depths is performed on a time interval of 12-48 h to be able to perform the necessary steps to alert and evacuate the population. Forecast results are available as web services. The proposed system extends the traditional separate methods based on satellite monitoring or modeling of a river's physical processes, by using an interdisciplinary approach, integration of different models and technologies, and through intelligent choice of the most suitable models for a flood forecasting.