In the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...

Embedded IoT networks are the backbone of safety-critical systems like smart factories, autonomous vehicles, and airplanes. Therefore, resilience against failures and attacks should be a prior concern already in their design stage. In this study, we introduce a service-based network model as an MILP optimization problem for the efficient deployment of a service overlay to the embedded network by meeting QoS and resilience requirements....

In this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...

Responding to the new phenomena in entrepreneurship ecosystems in Poland, the author undertakes the study that aims to explore experiences of participants of (pre)accelerator programme for start-ups. Clipster is a business an acceleration and incubation programme, where participants have a unique co-living opportunity and work on their new venture ideas. With phenomenological interviews with six nascent entrepreneurs - participants...