## 5 Conclusions  
In this research work, a bi-level and multi-objective procedure has been defined for the integrated optimization of the energy recovery and production system on board of a large cruise ship. This procedure is based on an external genetic optimization algorithm, which creates a population of individuals defined by genes, which correspond to the optimization variables that determine the presence or absence of the different components in the super-structure of the energy system. These values are acquired from the internal optimization level, based on a MILP procedure that can be solved with X-Press. The entire procedure has been implemented in the modeFRONTIER(r) platform, which allows the Pareto front of the optimization with two objective functions to be easily identify. In particular, fuel consumption during the cruise and an appropriate PENALTY function have been considered. The latter represents the volume occupied by the additional components dedicated to energy recovery. The use of the modeFRONTIER platform also allows an easy introduction of the specific inputs of each optimization (for example the range for the variables that represent the number of ORC and Stirling groups) and to perform a statistical analysis on all designs considered through the scattering matrix. The analysis of the results of the multi-objective optimization indicates that the summer and winter cruises require different solutions to optimize the ship's integrated energy generation and recovery system. In particular, in the summer solution, the ORC groups are not present or are reduced to a single 150 kW group; on the contrary, in the winter solution, the absence of the absorption chiller allows the use of excess heat to feed 9-10 ORC groups. Figure 17: SOx emissions values, calculated for the winter/summer cruise, with different strategies for the usage of fuel and abatement devices. Figure 18: NOx emissions values, calculated for the winter/summer cruise, with different strategies for the usage of fuel and abatement devices. Both optimal solutions, on the other hand, show about the same number (18-20) of 50 kW Stirling groups, with a total nominal power of 900-1000 kW. The hot water thermal storage (at about 90 \({}^{\circ}\)C) is very useful for the goal of reducing consumption, even if it involves a significant additional volume occupation; the size of the absorption chiller in the designs on the Pareto front is such as to cover about 90% (or more) of the refrigeration load required. In the summer case, the solutions on the Pareto front frequently show the value of 25,000 kWh for the size of the storage, i.e., the upper limit of the range considered, indicating that an even larger storage (closer to that found for the winter case--40,000 kWh) could allow better results. Compared to the approximately 11,000,000 kWh of energy estimated for the overall fuel consumption during the reference summer cruise, the reclassification of the thermal loads (consistently with the temperature levels actually required) together with the optimized management of the engine load along the cruise allow the consumption to be reduced to 10,688,000 kWh; the introduction of energy recovery devices allows, considering the ID 18 solution, to further reduce consumption to 10,101,700 kWh, with a saving of 8% compared to the estimated reference and 5.5% compared to the optimal solution, without recovery devices. Whilst, for the winter cruise, the reclassification of the thermal loads together with the optimized management of the engine load allow to reduce the overall fuel consumption to 11,986,000 kWh, compared to the 12,500,000 kWh estimated for the reference case; the introduction of energy recovery devices allows, considering the ID 210 solution, to further reduce consumption to 11,535,500 kWh, with a saving of 7.5% compared to the estimated reference and more than 3% compared to the optimal solution, without recovery devices. The decrease (almost 20%) in fuel consumption during the port stops of the summer cruise is certainly significant.