Fuzzy Optimal Allocation and Arrangement of Spaces in Naval Surface ShipDesign.

General Arrangements;Space Allocation;Optimization;Naval Surface Ship;Ship Design;Naval Architecture and Marine Engineering;Engineering;Naval Architecture & Marine Engineering

Nick, Eleanor KateTroesch, Armin W. ;

University of Michigan

关键词: General Arrangements;    Space Allocation;    Optimization;    Naval Surface Ship;    Ship Design;    Naval Architecture and Marine Engineering;    Engineering;    Naval Architecture & Marine Engineering;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/60736/enick_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

A new approach to generating, evaluating, and optimizing general arrangementsof naval surface ships is presented. Beginning from a user editable database of spaces,the algorithms return an optimized arrangement. The user drives the design by quantitativelydefining spaces’ goals and constraints for location, proximity, and shape.The arrangements task is undertaken in two parts: Allocation and Arrangement.Allocation is the assignment of a space to a region of a ship. The unit region used isdubbed a Zone-deck. The Zone-deck is the intersection of one deck and one watertightsubdivision. The allocation solution evaluates Zone-deck area utilization and spaces’relative and global position goals. Adjacency and separation distance between spacesis measured in increments of deck and subdivision. Global position is assessed bydeck and subdivision. Each discrete distance and position has an editable defaultfuzzy preference value. Allocation is essentially a very large scale combinatorial binpacking problem. With the added complexity of relative location constraints, thisalso becomes a type of quadratic assignment problem. The independent variablevector is an ordered listing by space index number of each space’s assigned Zonedeckindex number. A customized Genetic Algorithm optimizes the integer-codedchromosome.The second part arranges one Zone-deck at a time. Arrangement is done in twoiterative steps: topology and geometry. Topology gives the relative longitudinal and transverse position of each space’s seed location. These locations are translated ontoan orthogonal grid. In the second step, spaces are expanded to have size and shapefilling the available area in the stochastic growth loop. Spaces are defined by up tothree contiguous boxes allowing for L, T, C and Z shapes. The arrangement costfunction evaluates each space’s required area satisfaction, aspect ratio, minimumoverall dimension, minimum segment dimension, perimeter, connectivity to access,and proximity constraints to other spaces. Editable piecewise linear fuzzy utilityfunctions translate each criteria measure to a fuzzy utility. The best of a modestnumber of geometry solutions returns joiner bulkhead locations and a cost functionvalue to a Genetic Algorithm optimization of the topology chromosome.