%PDF-1.5
%
1 0 obj
<<
/Metadata 2 0 R
/Names 3 0 R
/OpenAction 4 0 R
/Outlines 5 0 R
/PageMode /UseNone
/Pages 6 0 R
/Type /Catalog
/ViewerPreferences <<
/FitWindow true
>>
>>
endobj
7 0 obj
<<
/Author (Cemre Cubukcuoglu, Ioannis Chatzikonstantinou, Mehmet Fatih Tasgetiren, I. Sevil Sariyildiz and Quan-Ke Pan)
/CreationDate (D:20160730113330+08'00')
/Creator (LaTeX with hyperref package)
/Keywords (evolutionary computation; harmony search algorithm; computational design; floating city optimization; performance-based design; multi-objective optimization)
/ModDate (D:20161026131015+02'00')
/PTEX.Fullbanner (This is pdfTeX, Version 3.14159265-2.6-1.40.15 \(TeX Live 2014/W32TeX\) kpathsea version 6.2.0)
/Producer (pdfTeX-1.40.15)
/Subject (This paper is concerned with the application of computational intelligence techniques to the conceptual design and development of a large-scale floating settlement. The settlement in question is a design for the area of Urla, which is a rural touristic region located on the west coast of Turkey, near the metropolis of Izmir. The problem at hand includes both engineering and architectural aspects that need to be addressed in a comprehensive manner. We thus adapt the view as a multi-objective constrained real-parameter optimization problem. Specifically, we consider three objectives, which are conflicting. The first one aims at maximizing accessibility of urban functions such as housing and public spaces, as well as special functions, such as a marina for yachts and a yacht club. The second one aims at ensuring the wind protection of the general areas of the settlement, by adequately placing them in between neighboring land masses. The third one aims at maximizing visibility of the settlement from external observation points, so as to maximize the exposure of the settlement. To address this complex multi-objective optimization problem and identify lucrative alternative design solutions, a multi-objective harmony search algorithm \(MOHS\) is developed and applied in this paper. When compared to the Differential Evolution algorithm developed for the problem in the literature, we demonstrate that MOHS achieves competitive or slightly better performance in terms of hyper volume calculation, and gives promising results when the Pareto front approximation is examined.)
/Title (A Multi-Objective Harmony Search Algorithm for Sustainable Design of Floating Settlements "2279)
/Trapped /False
>>
endobj
2 0 obj
<<
/Length 5806
/Subtype /XML
/Type /Metadata
>>
stream
application/pdf
Cemre Cubukcuoglu, Ioannis Chatzikonstantinou, Mehmet Fatih Tasgetiren, I. Sevil Sariyildiz and Quan-Ke Pan
This paper is concerned with the application of computational intelligence techniques to the conceptual design and development of a large-scale floating settlement. The settlement in question is a design for the area of Urla, which is a rural touristic region located on the west coast of Turkey, near the metropolis of Izmir. The problem at hand includes both engineering and architectural aspects that need to be addressed in a comprehensive manner. We thus adapt the view as a multi-objective constrained real-parameter optimization problem. Specifically, we consider three objectives, which are conflicting. The first one aims at maximizing accessibility of urban functions such as housing and public spaces, as well as special functions, such as a marina for yachts and a yacht club. The second one aims at ensuring the wind protection of the general areas of the settlement, by adequately placing them in between neighboring land masses. The third one aims at maximizing visibility of the settlement from external observation points, so as to maximize the exposure of the settlement. To address this complex multi-objective optimization problem and identify lucrative alternative design solutions, a multi-objective harmony search algorithm (MOHS) is developed and applied in this paper. When compared to the Differential Evolution algorithm developed for the problem in the literature, we demonstrate that MOHS achieves competitive or slightly better performance in terms of hyper volume calculation, and gives promising results when the Pareto front approximation is examined.
A Multi-Objective Harmony Search Algorithm for Sustainable Design of Floating Settlements "2279
2016-07-30T11:33:30+08:00
LaTeX with hyperref package
2016-10-26T13:10:15+02:00
2016-10-26T13:10:15+02:00
evolutionary computation; harmony search algorithm; computational design; floating city optimization; performance-based design; multi-objective optimization
pdfTeX-1.40.15
False
This is pdfTeX, Version 3.14159265-2.6-1.40.15 (TeX Live 2014/W32TeX) kpathsea version 6.2.0
uuid:12e2d268-ed70-4a74-9234-31ab97e42ffd
uuid:4489065a-0469-4b7e-9ef5-1376f01f7f0c
endstream
endobj
3 0 obj
<<
/Dests 8 0 R
>>
endobj
4 0 obj
<<
/D [9 0 R /FitH]
/S /GoTo
>>
endobj
5 0 obj
<<
/Count 7
/First 10 0 R
/Last 11 0 R
/Type /Outlines
>>
endobj
6 0 obj
<<
/Count 18
/Kids [12 0 R 13 0 R 14 0 R]
/Type /Pages
>>
endobj
8 0 obj
<<
/Kids [15 0 R 16 0 R 17 0 R 18 0 R]
/Limits [(AMS.1) (table.1)]
>>
endobj
9 0 obj
<<
/Annots [19 0 R 20 0 R 21 0 R]
/Contents [22 0 R 23 0 R 24 0 R 25 0 R 26 0 R 27 0 R 28 0 R 29 0 R]
/CropBox [0 0 595.276 841.89]
/MediaBox [0 0 595.276 841.89]
/Parent 12 0 R
/Resources 30 0 R
/Rotate 0
/Type /Page
>>
endobj
10 0 obj
<<
/A 31 0 R
/Next 32 0 R
/Parent 5 0 R
/Title
>>
endobj
11 0 obj
<<
/A 33 0 R
/Parent 5 0 R
/Prev 34 0 R
/Title
>>
endobj
12 0 obj
<<
/Count 7
/Kids [35 0 R 9 0 R 36 0 R 37 0 R 38 0 R 39 0 R 40 0 R]
/Parent 6 0 R
/Type /Pages
>>
endobj
13 0 obj
<<
/Count 6
/Kids [41 0 R 42 0 R 43 0 R 44 0 R 45 0 R 46 0 R]
/Parent 6 0 R
/Type /Pages
>>
endobj
14 0 obj
<<
/Count 5
/Kids [47 0 R 48 0 R 49 0 R 50 0 R 51 0 R]
/Parent 6 0 R
/Type /Pages
>>
endobj
15 0 obj
<<
/Kids [52 0 R 53 0 R 54 0 R 55 0 R 56 0 R 57 0 R]
/Limits [(AMS.1) (Item.14)]
>>
endobj
16 0 obj
<<
/Kids [58 0 R 59 0 R 60 0 R 61 0 R 62 0 R 63 0 R]
/Limits [(Item.15) (cite.B4-algorithms-09-00051)]
>>
endobj
17 0 obj
<<
/Kids [64 0 R 65 0 R 66 0 R 67 0 R 68 0 R 69 0 R]
/Limits [(cite.B5-algorithms-09-00051) (page.2)]
>>
endobj
18 0 obj
<<
/Kids [70 0 R 71 0 R 72 0 R]
/Limits [(page.3) (table.1)]
>>
endobj
19 0 obj
<<
/A <<
/S /URI
/Type /Action
/URI (http://www.mdpi.com/journal/algorithms)
>>
/Border [0 0 0]
/C [0 1 1]
/H /I
/Rect [75.539 757.64 207.93 793.648]
/Subtype /Link
/Type /Annot
>>
endobj
20 0 obj
<<
/A <<
/S /URI
/Type /Action
/URI (http://www.mdpi.com)
>>
/Border [0 0 0]
/C [0 1 1]
/H /I
/Rect [474.736 757.64 519.737 793.648]
/Subtype /Link
/Type /Annot
>>
endobj
21 0 obj
<<
/A <<
/S /URI
/Type /Action
/URI (http://www.mdpi.com/journal/algorithms)
>>
/Border [0 0 0]
/C [0 1 1]
/H /I
/Rect [387.625 39.132 519.737 49.282]
/Subtype /Link
/Type /Annot
>>
endobj
22 0 obj
<<
/Length 489
/Filter /FlateDecode
>>
stream
HSMo0+|ܭ/l|L%JQՆ[K>T0_A+TH0{T"n# q1o#B%qK.QQG#,bhN6\\kLu:"M4K
fB%XqU 4֒IFRXp=٢2ٗ-UXs`1I%dw7T_Ln7yW}|YmgݹSۍ|`5/?.M~Bk۲q{ߛ͝mʙȹԦqSK.x`ԓ<0"bO