Design of tool for the optimization of deck area assignments with integration into existing naval ship design programs

Many tasks in the early stages of ship design are manual and repetitive processes. One such task is in the realm of deck area arrangements. The allocation and assignment of areas in early stage ship design involves tracking the difference of total ship area envelope and all required areas to be placed for habitability, mission support, and propulsion capability among many. The problem becomes more complex with the addition of constraints involving required separation zones between other areas, affinities for certain areas or deck levels, and compartment subdivision. The Leading Edge Architecture for Prototyping Systems (LEAPS) database structure output from the Advanced Ship and Submarine Evaluation Tool (ASSET) provides a ship envelope and a list of areas requiring assignment. However, with over a hundred different area categories to place in a subdivided ship hull of a large number of compartments each with their own preferences and constraints, this problem is categorized as Nondeterministic Polynomial-time hard (NP-hard). A complete solution to an NP-hard problem cannot be found in polynomial time, meaning that finding the optimal solution in the design space is not realistically feasible as the problem scales upwards in size. Fortunately this type of problem, known as Bin Packing, is well understood in computer science. Metaheuristic methods of obtaining near-optimal solutions in a finite timeframe exist that are reasonable enough for use. This thesis presents a ship design tool that pairs two of these meta-heuristic methods with naval ship architecture and LEAPS based projects. The approach is divided into three major steps: a ship volume balance, a ship area balance, and an area layout of the ship footprint. The output of the tool is the general arrangements drawings in a universal CAD format that would be the starting point for more detailed arrangements.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Oslebo, Damian G

Advisor dc:contributor.advisor

• Chryssostomos Chryssostomidis and Fredo Durand.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/92104

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/92104