COMPIT 2004 in Siguenza/ Spain - Institut für Entwerfen von ...

2. Generation
The generation of solutions is rather a creative task. While “Artificial Intelligence” is by now widely
accepted as an additional useful tool also for naval architects, nobody contemplates (seriously)
“Artificial Creativity”. And yet the computer may help us to generate better solutions, namely in the
context of concept exploration and/or optimization, Bertram (2003a).
A concept exploration models (CEM) generates a large set of candidate solutions by varying design
variables. Each of these solutions is evaluated, stored and graphically displayed, so that the designer
gets a feeling how certain variables influence the performance of the design, e.g. Erikstad (1996).
This preliminary “exploration” is often necessary to determine suitable optimization objectives and
constraints. This approach, albeit under the misleading label of “multi-objective optimization” is realized
in the modeFRONTIER optimization environment, e.g. Abt et al. (2003). The approach is in reality
a preliminary concept exploration generating many solutions and defining Pareto surfaces , Fig.2,
which then allow the user to reject certain solutions (realizing at this stage constraints which were so
far not explicitly stated) and finding an “optimum” solution (within the more or less simplified optimization
model using more or less erroneous approximations for evaluating candidate properties).
Despite remaining short-comings, optimization shells as modeFRONTIER or the German development
DELPHI, e.g. Bertram et al. (1998), Gudenschwager (2003), allow the designer to focus on the
design task and allow by now models of suitable complexity to indeed aid the practical design process.
Setting up a suitable optimization model, rather than programming yet another optimization algorithm,
is the task for the naval architect.
Fig.2: Result of form optimization with Pareto
Frontier for FantaRoRo, source: TU Berlin
Fig.3: Schenzle’s ‘design for production’ hull,
Bertram and El Moctar (2003)
New and improved simulation tools can be integrated in optimization models allowing new or more
realistic applications. Possibilities are as numerous as the rapidly developing simulation tools. Examples
from my own research interest and experience include:
• Hull production costs are so far rarely quantified in the design. Bottom-up approaches (decomposing
the production process into appropriate subtasks like profile and plate bending,
welding in various positions and techniques, etc.) are needed to suitably reflect the influence
of local hull shape changes, Bertram and El Moctar (2003). Rigo (2003) presents how bottom-up
approaches can now be applied successfully to support shipyard structural design
work. Hulls optimized for production costs without hydrodynamic sacrifices appear feasible,
Fig.3.
• Optimization uses often an economic criterion. Ships have been optimized in the past for
building costs (“shipyard’s view”) or yield including operational cost and income (“ship
owner’s view”). Environmental aspects have been largely neglected in optimization with the
notable exception of wash, e.g. Koushan et al. (2002). However, ship emissions cause indi-
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