Kaklis Dimitrios

Routing Optimization in Maritime Industry:
Coupling Data Mining with Machine Learning Algorithms in the Context of a Non-Convex Regulated Regression Estimated Problem

The maximization of exergy in maritime transportation without additional investment just by intelligent reduction of the consumed energy to overcome added resistance due to weather factors; and even more: the transformation of the
exergy, technically defined, function to a profit-utility function including the time as well as marketing data, that is the exergy of the corresponding financial system.
FF ANN (Feed forward artificial neural network) and big data analytics will be designed and be developed for source-agnostic interoperability, eliminating vessels’-specific consumed time and cost theoretical hydrodynamic model.
Algorithms to find the best seaway under calm weather conditions between any two waypoints, that avoids lands, restricted areas, war zones, draft limitations and navigation rules.