# Developments, Trends, and Challenges in Optimization of Ship Energy Systems
## Closure  
Optimization of energy systems on land started being applied in the 1970s with continuous development since that time. The triple optimization (synthesis, design, and operation), in particular, has been formally stated and started being developed and applied about 20 years later, again on land installations. If the journal article search performed with this opportunity has not missed related contributions, optimization of energy systems on ships appeared in the first decade of the 21 st century. Significant developments in methodologies, algorithms, and applications have been achieved up to now, while further research needs and challenges are required, as explained in Sections 5 and 6; it is worth summarizing those here:  
* Synthesis optimization is always a challenging endeavor: how to support and/or replace the designer's experience, ingenuity, and inspiration with a computer code?
* Further development of both superconfiguration-based and superconfiguration-free methods for synthesis optimization is needed.
* Synthesis optimization of working fluids has appeared recently on land installations. Its incorporation in the synthesis optimization of the whole system is worth pursuing.
* There is need of further development of methods for SDO optimization of ship energy systems taking into consideration
* uncertainties (e.g., in operating profile, cost of fuel, weather conditions, etc.),
* reliability-availability of equipment,
* combinations of the preceding.
* Interdisciplinary approach needs to be followed, so that aspects not only of mechanical engineering but also of other disciplines such as electrical and control engineering are taken into consideration in optimization.
* The border of the system to be optimized needs to be further and further expanded, with the aim of including the ship as a whole.  
The preceding makes it rather clear that there are many interesting and challenging subjects that need to be addressed, and there are areas for further development of methodology combined with applications on ship energy systems.  
**Funding:** This research received no external funding.  
**Conflicts of Interest:** The author declares no conflict of interest.  
**Symbols and Abbreviations**  
A Heat transfer area  
AC Alternating current  
Adaptive Multicontext Cooperatively Coevolving Particle Swarm  
Optimization Algorithm  
APC Absorption Power Cycle  
AR Absorption Refrigeration  
BOG Boil-Off Gas  
COBYLA Constraint Optimization BY Linear Approximation  
COGES Combined Gas turbine, Electric generator and Steam turbine  
CPP Controllable Pitch Propeller  
D Design  
DC Direct current  
DDP Deterministic Dynamic Programming  
DE Diesel engine  
DF Dual fuel  
DGiesel-generator  
DSO\({}_{\rm x}\) Desulfphurization  
DNO\({}_{\rm x}\) Denitrification  
\(\Delta Ex\) total exergy supplied to the system  
EEDI Energy Efficiency Design Index  
EEOI Energy Efficiency Operational Indicator  
EG Exhaust gas  
EGR Exhaust gas recirculation  
ESS Energy storage system  
FC Fuel cell  
fmincon Find minimum of constrained nonlinear multivariable function  
FPP Fixed pitch propeller  
GAMS General Algebraic Modeling System  
GE Genetic Algorithm  
GHG Greenhouse gas  
GRG Generalized Reduced Gradient  
GT Gas turbine  
GWP Global Warming Potential  
GUROBI [PERSON], [PERSON], [PERSON]**[PERSON]  
HESS Hybrid Energy Storage System  
HRSG Heat Recovery Steam Generator  
IES Integrated Energy System  
INTLAB Interval Laboratory  
ISCA Improved Sine Cosine Algorithm  
JCW Jacket cooling water  
JW Jacket water  
KC Kalina cycle  
LNG Liquefied natural gas  
MCFC Molten Carbonate Fuel Cell  
MCR Maximum Continuous Rating  
MIDACO Mixed Integer Distributed Ant Colony Optimization Solver  
MINLP Mixed Integer Nonlinear Programming  
MOPSO Multiobjective Particle Swarm Optimization