edit 29/04/14 - Here is a new collection of more than 80 example files, organized by category:
KangarooExamples.zip
This zip is the most up to date collection of examples at the moment, and collects t
es has guided me in a - what I once thought - specific path within architecture, but recent discoveries (like the Grasshopper-community etc.) have learned me that the field of digital and parametric architecture is so-to-speak alive and kicking. This is also the main subject I would like to write my thesis about. It is however mainly the subject and defining its boundaries – what do I really want to explore and research? – which is the most difficult factor at this time.
A concrete idea is non-existant, and my current visions will probably be redirected when I have a first meeting with the promotors in February. Moreover there is the knowledge that it is impossible to make a thesis at the institute in Antwerp on no matter what subject in the world of digital architecture. Understandably too, it’s a small world and does not always result in realised projects, but in impressive imagery. At this moment however, I am thinking of two possible research fields to focus on.
In a first option the focus might lie on how digital design tools can be used to bring a certain aspect of interactivity to building facades. Such interactivity can occur both in the design phase and throughout the use of the building. The first scenario, in which the interactivity occurs when designing, I would focus on how the designer can shape a building’s outer perspective in function of environmental parameters: obstacles, elements that block sunlight from entering the building, visually important landmarks, etc. It should be noted however that focus will mostly lie on the design element, and less on the energy-efficiency and sustainability. Tools that will be researched would include Grasshopper, Rhino Scripting, Processing and ParaCloud.
A second possible approach could be categorized under both Swarm Intelligence and Generative Design and might study how the aforementioned digital techniques might be implemented in the new urbanism. We notably see more (innovative) interventions in which the design and planning is heavily influenced by movement patterns and morphogenetic parameters and functions. Based on the outcome of these scripted techniques, designers tend to work towards a proposal which answers a certain urbanistic issue.
All additional insights, guidelines, tips, comments are more than welcome in order to help me define the scope of my thesis subject. I must admit I am pretty new to this digital design world (it is not actively promoted at my home university, but it is promoted at the university where I am studying for one year now) and thus have limited experience at the time of writing.
Please also feel free to check out the blog post concerning this topic, which is a little more elaborate: http://nielswouters.be/thesis-digital-design-english/
Thanks for all your help!
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mplex the models are. If we are running multi-room E+ studies, that will take far longer to calculate.
Rhino/Grasshopper = <1%
Generating Radiance .ill files = 88%
Processing .ill files into DA, etc. = ~2%
E+ = 10%
Parallelizing Grasshopper:
My first instinct is to avoid this problem by running GH on one computer only. Creating the batch files is very fast. The trick will be sending the radiance and E+ batch files to multiple computers. Perhaps a “round-robin” approach could send each iteration to another node on the network until all iterations are assigned. I have no idea how to do that but hope that it is something that can be executed within grasshopper, perhaps a custom code module. I think GH can set a directory for Radiance and E+ to save all final files to. We can set this to a local server location so all runs output to the same location. It will likely run slower than it would on the C:drive, but those losses are acceptable if we can get parallelization to work.
I’m concerned about post-processing of the Radiance/E+ runs. For starters, Honeybee calculates DA after it runs the .ill files. This doesn’t take very long, but it is a separate process that is not included in the original Radiance batch file. Any other data manipulation we intend to automatically run in GH will be left out of the batch file as well. Consolidating the results into a format that Design Explorer or Pollination can read also takes a bit of post-processing. So, it seems to me that we may want to split up the GH automation as follows:
Initiate
Parametrically generate geometry
Assign input values, material, etc.
Generate radiance/ E+ batch files for all iterations
Calculate
Calc separate runs of Radiance/E+ in parallel via network clusters. Each run will be a unique iteration.
Save all temp files to single server location on server
Post Processing
Run a GH script from a single computer. Translate .ill files or .idf files into custom metrics or graphics (DA, ASE, %shade down, net solar gain, etc.)
Collect final data in single location (excel document) to be read by Design Explorer or Pollination.
The above workflow avoids having to parallelize GH. The consequence is that we can’t parallelize any post-processing routines. This may be easier to implement in the short term, but long term we should try to parallelize everything.
Parallelizing EnergyPlus/Radiance:
I agree that the best way to enable large numbers of iterations is to set up multiple unique runs of radiance and E+ on separate computers. I don’t see the incentive to split individual runs between multiple processors because the modular nature of the iterative parametric models does this for us. Multiple unique runs will simplify the post-processing as well.
It seems that the advantages of optimizing matrix based calculations (3-5 phase methods) are most beneficial when iterations are run in series. Is it possible for multiple iterations running on different CPUs to reference the same matrices stored in a common location? Will that enable parallel computation to also benefit from reusing pre-calculated information?
Clustering computers and GPU based calculations:
Clustering unused computers seems like a natural next step for us. Our IT guru told me that we need come kind of software to make this happen, but that he didn’t know what that would be. Do you know what Penn State uses? You mentioned it is a text-only Linux based system. Can you please elaborate so I can explain to our IT department?
Accelerad is a very exciting development, especially for rpict and annual glare analysis. I’m concerned that the high quality GPU’s required might limit our ability to implement it on a large scale within our office. Does it still work well on standard GPU’s? The computer cluster method can tap into resources we already have, which is a big advantage. Our current workflow uses image-based calcs sparingly, because grid-based simulations gather the critical information much faster. The major exception is glare. Accelerad would enable luminance-based glare metrics, especially annual glare metrics, to be more feasible within fast-paced projects. All of that is a good thing.
So, both clusters and GPU-based calcs are great steps forward. Combining both methods would be amazing, especially if it is further optimized by the computational methods you are working on.
Moving forward, I think I need to explore if/how GH can send iterations across a cluster network of some kind and see what it will take to implement Accelerad. I assume some custom scripting will be necessary.…
oftware connections built from the initial seed of the project. As always you can download the new release from Food4Rhino. Make sure to remove the older version of Ladybug and Honeybee and update your scripts.
This release is also special since today it is just about 3 years (3 years and 2 weeks) from the first release of Ladybug. As with any release, there have been a number of bug fixes and improvements but we also have some major news this time. In no specific order and to ensure that the biggest developments do not get lost in the extensive list of updates, here are the major ones:
Mostapha is re-writing Ladybug!
Ladybug for DynamoBIM is finally available.
Chris made bakeIt really useful by incorporating an export pathway to PDFs and vector-based programs.
Honeybee is now connected to THERM and the LBNL suite thanks to Chris Mackey.
Sarith has addressed a much-desired wish for Honeybee (Hi Theodore!) by adding components to model electric lighting with Radiance.
Djordje is on his way to making renewable energy deeply integrated with Ladybug by releasing components for modeling solar hot water.
There is new bug. Check the bottom of the post for Dragonfly!
Last but definitely not least (in case you’re not still convinced that this release is a major one) Miguel has started a new project that brings some of Ladybug’s features directly to Rhino. We mean Rhino Rhino - A Rhino plugin! Say hi to Icarus! #surprise
Before we forget! Ladybug and Honeybee now have official stickers. Yes! We know about T-Shirts and mugs and they will be next. For now, you can deck-out your laptops and powerhouse simulation machines with the symbology of our collaborative software ecosystem.
Now go grab a cup of tea/coffee and read the details below:
Rewriting Ladybug!
Perhaps the most far-reaching development of the last 4 months is an effort on the part of Mostapha to initiate a well structured, well documented, flexible, and extendable version of the Ladybug libraries. While such code is something that few community members will interact with directly, a well-documented library is critical for maintaining the project, adding new features, and for porting Ladybug to other software platforms.
The new Ladybug libraries are still under development across a number of new repositories and they separate a ladybug-core, which includes epw parsing and all non-geometric functions, from interface-specific geometry libraries. This allows us to easily extend Ladybug to other platforms with a different geometry library for each platform (ie. ladybug-grasshopper, ladybug-dynamo, ladybug-web, etc) all of which are developed on top of the ladybug-core.
Without getting too technical, here is an example of a useful outcome of this development. If you want to know the number of hours that relative humidity is more than 90% for a given epw, all that you have to code (in any python interface) is the following:
import ladybug as lb
_epwFile = r"C:\EnergyPlusV7-2-0\WeatherData\USA_CO_Golden-NREL.724666_TMY3.epw"
epwfile = lb.epw.EPW(_epwFile)
filteredData = epwfile.relativeHumidity.filterByConditionalStatement('x>90')
print "Number of hours with Humidity more than 90 is %d "%len(filteredData.timeStamps)
Compare that to the 500 + lines that you would have had to write previously for this operation, which were usually tied to a single interface! Now let’s see what will happen if you want to use the geometry-specific libraries. Let’s draw a sunpath in Grasshopper:
import ladybuggrasshopper.epw as epw
import ladybuggrasshopper.sunpath as sunpath
# get location data form epw file
location = epw.EPW(_epwFile).location
# initiate sunpath based on location
sp = sunpath.Sunpath.fromLocation(location, northAngle = 0, daylightSavingPeriod = None, basePoint =cenPt, scale = scale, sunScale = sunScale)
# draw sunpath geometry
sp.drawAnnualSunpath()
# assign geometries to outputs
...
Finally we ask, how would this code will look if we wanted to make a sunpath for dynamo? Well, it will be exactly the same! Just change ladybuggrasshopper in the second line to ladybugdynamo! Here is the code which is creating the sunpath below.
With this ease of scripting, we hope to involve more of our community members in our development and make it easy for others to use ladybug in their various preferred applications. By the next release, we will produce an API documentation (documentation of all the ladybug classes, methods and properties that you can script with) and begin making tutorials for those interested in getting deeper into Ladybug development.
LADYBUG
1 - Initial Release of Ladybug for Dynamo:
As is evident from the post above, we are happy to announce the first release of Ladybug for Dynamo! You can download the ladybug package from Dynamo package manager. Make sure to download version 0.0.6 which is actually 0.0.1! It took a number of trial and errors to get it up there. Once you have the file downloaded you can watch these videos to get started:
The source code can be find under ladybug-dynamo repository and (as you can already guess) it is using the new code base. It includes a very small toolkit of essential Ladybug components/nodes but it has enough to get you started. You can import weather files, draw sunpaths and run sunlighthours or radiation analyses.
There are two known issues in this release but neither of them is critical. You need to have Dynamo 0.9.1 or higher installed which you can download from here (http://dynamobuilds.com/). It is recommended that you run the scripts with ‘Manual’ run (as opposed to ‘Automatic’) since the more intense calculations can make Dynamo crash in automatic mode.
To put things in perspective, here is how we would map Ladybug for Dynamo vs Ladybug and Honeybee for Grasshopper on the classic ‘Hype graph’. The good news is that what we learned a lot from the last three years, making development of the Dynamo version easier and getting us to the plateau of productivity faster.
We should also note that the current development of the Dynamo interface is behind that of the Ladybug-Core, which means there are a number of features that are developed in the code but haven’t made their way to the nodes yet. They will be added gradually over the next month or two.
If you’re interested to get involved in the development process or have ideas for the development, follow ladybug on Facebook, Twitter and Github. We will only post major release news here. Facebook, github and twitter will be the main channels for posting the development process. There will also be a release of a new ladybug for Grasshopper soon that will use the came Ladybug-Core libraries as the Dynamo interface [Trying hard not to name it as Ladybug 2].
2 - New Project “Icarus” Provides Ladybug Capabilities Directly in Rhino
Speaking of expanded cross-platform capabilities, the talented Miguel Rus has produced a standalone Rhino Plugin off of the original Ladybug code that has been included in this release. After writing his own core C# libraries, Miguel’s plugin enables users to produce sunpath and run sunlight hours analyses in the Rhino scene without need of opening Grasshopper or engaging the (sometimes daunting) act of visual scripting.
This release includes his initial RHP plugin file. It is hoped that Miguel’s efforts will extend some of the capabilities of environmental design to individuals who are unfamiliar with visual scripting, casting the network of our community into new territory. We need your help spreading the word about Icarus since the people who will benefit the most from it have probably not read this far into the release notes. Also, as the project is in the early stages, your feedback can make a great difference. You can download the current release from this link.
Once you download the zip file. Right click and unblock it. Then extract the files under C:\Program Files\Rhinoceros 5 (64-bit)\Plug-ins\ folder. Drag and drop the RHP file into Rhino and you should be ready to go. You can either type Icarus in the command line or open it via the panels. Here is a short video that shows how to run a sunlighhours analysis study in Rhino.
3 - BakeIt Input Now Supports a Pathway to PDF +Vector Programs
As promised in the previous release, the BakeIt_ option available on Ladybug’s visual components has been enhanced to provide a full pathway to vector-based programs (like Illustrator and Inkscape) and eases the export to vector formats like PDFs.
This means that the BakeIt_ operation now places all text in the Rhino scene as actual editable text (not meshes) and any colored meshes are output as groups of colored hatches (so that they appear as color-filled polygons in vector-based programs). There is still an option to bake the colored geometries as light meshes (which requires smaller amounts of memory and computation time) but the new hatched capability should make it easier to incorporate Ladybug graphics in architectural drawings and documents like this vector psychrometric chart.
4 - Physiological Equivalent Temperature (PET) Now Available
Thanks to the efforts of Djordje Spasic, it is now possible to compute the common outdoor comfort metric ‘Physiological Equivalent Temperature’ (PET) with Ladybug. The capability has been included with this release of “Thermal Comfort Indices” component and is supported by a “Body Characteristics” component in the Extra tab. PET is particularly helpful for evaluating outdoor comfort at a high spatial resolution and so the next Honeybee release will include an option for PET with the microclimate map workflow.
5 - Solar Hot Water Components Available in WIP
Chengchu Yan and Djordje Spasic have built a set of components that perform detailed estimates of solar hot water. The components are currently undergoing final stages of testing and are available in the WIP tab of this release. You can read the full release notes for the components here.
6 - New Ladybug Graphic Standards
With the parallel efforts or so many developers, we have made an effort in this release to standardize the means by which you interact with the components. This includes warnings for missing inputs and the ability to make either icons or text appear on the components as you wish (Hi Andres!). A full list of all graphic standards can be found here. If you have any thoughts or comments on the new standards, feel free to voice them here.
7 - Wet Bulb Temperature Now Available
Thanks to Antonello Di Nunzio - the newest member of the Ladybug development team, it is now possible to calculate wet bulb temperature with Ladybug. Antonello’s component can be found under the WIP tab and takes inputs of dry bulb temperature, relative humidity, and barometric pressure.
8 - New View Analysis Types
The view analysis component now allows for several different view studies in addition to the previous ‘view to test points.’ These include, skyview (which is helpful for studies of outdoor micro-climate), as well as spherical view and ‘cone of vision’ view, which are helpful for indoor studies evaluating the overall visual connection to the outdoors.
HONEYBEE
1 - Connection to THERM and LBNL Programs
With this release, many of you will notice that a new tab has been added to Honeybee. The tab “11 | THERM” includes 7 new components that enable you to export ready-to-simulate Lawrence Berkeley National Lab (LBNL) THERM files from Rhino/Grasshopper. THERM is a 2D finite element heat flow engine that is used to evaluate the performance of wall/window construction details by simulating thermal bridging behavior. The new Honeybee tab represents the first ever CAD plugin interface for THERM, which has been in demand since the first release of LBNL THERM several years ago. The export workflow involves the drawing of window/wall construction details in Rhino and the assigning of materials and boundary conditions in Grasshopper to produce ready-to-simulate THERM files that allow you to bypass the limited drawing interface of THERM completely. Additional components in the “11 | THERM” tab allow you to import the results of THERM simulations back into Grasshopper and assist with incorporating THERM results into Honeybee EnergyPlus simulations. Finally, two components assist with a connection to LBNL WINDOW for advanced modeling of Glazing constructions. Example files illustrating many of the capabilities of the new components can be found in there links.
THERM_Export_Workflow, THERM_Comparison_of_Stud_Wall_Constructions
Analyze_THERM_Results, Thermal_Bridging_with_THERM_and_EnergyPlus
Import_Glazing_System_from_LBNL_WINDOW, Import_LBNL_WINDOW_Glazing_Assembly_for_EnergyPlus
It is recommended that those who are using these THERM components for the first time begin by exploring this example file.
Tutorial videos on how to use the components will be posted soon. A great deal of thanks is due to the LBNL team that was responsive to questions at the start of the development and special thanks goes to Payette Architects, which allowed Chris Mackey (the author of the components) a significant amount of paid time to develop them.
2 - Electrical Lighting Components with Enhanced Capabilities for Importing and Manipulating IES Files
Thanks to the efforts of Sarith Subramaniam, it is now much easier and more flexible to include electric lighting in Honeybee Radiance simulations. A series of very exciting images and videos can be found in his release post.
You can find the components under WIP tab. Sarith is looking for feedback and wishes. Please give them a try and let him know your thoughts. Several example files showing how to use the components can be found here. 1, 2, 3.
3- Expanded Dynamic Shade Capabilities
After great demand, it is now possible to assign several different types of control strategies for interior blinds and shades for EnergyPlus simulations. Control thresholds range from zone temperature, to zone cooling load, to radiation on windows, to many combinations of these variables. The new component also features the ability to run EnergyPlus simulations with electrochromic glazing. An example file showing many of the new capabilities can be found here.
Dragonfly Beta
In order to link the capabilities of Ladybug + Honeybee to a wider range of climatic data sets and analytical tools, a new insect has been initiated under the name of Dragonfly. While the Dragonfly components are not included with the download of this release, the most recent version can be downloaded here. An example file showing how to use Dragonfly to warp EPW data to account for urban heat island effect can also be found here. By the next release, the capabilities of Dragonfly should be robust enough for it to fly on its own. Additional features that will be implemented in the next few months include importing thermal satellite image data to Rhino/GH as well as the ability to warp EPW files to account for climate change projections. Anyone interested in testing out the new insect should feel free to contact Chris Mackey.
And finally, it is with great pleasure that we welcome Sarith and Antonello to the team. As mentioned in the above release notes, Sarith has added a robust implementation for electric light modeling with Honeybee and Antonello has added a component to calculate wet bulb temperature while providing stellar support to a number of people here on the GH forum.
As always let us know your comments and suggestions.
Enjoy!
Ladybug+Honeybee development team
PS: Special thanks to Chris for writing most of the release notes!…
y in English. ○Presenter
Robert (Bob) McNeel (McNeel & Associates founder) Robert (Bob) McNeel is the founder and president of Robert McNeel & Associates (RMA). Founded in 1978, RMA originally focused on developing accounting software for accounting, architecture, engineering, and other personal services firms. Within a few years, RMA expanded its services to include selling and supporting microprocessor-based engineering and design software including AutoCAD. By 1985, the main focus of the business had shifted to AutoCAD sales, service, training, and software development. Bob McNeel grew up in the mountains of southern Washington State on a subsistence dairy farm. To pay for college, he worked in construction as a carpenter, welder, and cement finisher. Bob has a BA in Accounting from Washington State University. Prior to founding McNeel & Associates, he was a practicing Certified Public Accountant and the comptroller for a large construction company in Spokane. Andrés González (Rhino Fablab director) Andrés is a software trainer and developer since the 1980s. He has developed applications for diverse design markets as well as training materials for different CAD and Design software including the community of training materialswww.Rhino3D.TV Andrés has been working with the Rhino Team since the very early stages. He is now the head of the McNeel Southeast US & Latin American Division. He is the worldwide director of the digital fabrication community called RhinoFabLabwww.RhinoFabLab.com as well as the Generative Jewelry & Fashion Design community GJD3D www.GJD3d.com and Generative Furniture Design community GFD3D www.GFD3d.com 1981 -1985 University of North Carolina at Charlotte N.C. - EE.UU. B.S., Bachelor of Science in Engineering
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Added by Yusuke Oono at 9:28pm on October 16, 2013
eventually found out about genetic algorithms on which I found extensive researches, projects,... ! I looked into it and ended up on a few papers which I believe are the jumpstart for my master thesis.
"Galapagos; on the logic and limitations of generic solvers" by David RuttenArticle in Architectural Design 83(2) March 2013
"Black-box optimisation methods for architectural design" by Thomas Wortmann and Giacomo NanniciniConference Paper: CAADRIA 2016, At Melbourne, AU, Volume: 177-186
So I started looking into alternatives to genetic algorithms in architectural design.So far, I've ended up on :
Thomas Wortmann's work with the surrogate(or model) based optimization approach!You can check out the tool he developped for GH (Opossum):http://www.food4rhino.com/app/opossum-optimization-solver-surrogate-models
Judyta Cichocka's work, specially with the Swarm approachYou can check out the tool she developped for GH (Silvereye):http://www.food4rhino.com/app/silvereye-pso-based-solver
And that's it !!! I've been researching through article references (mainly on "researchgate") but I'm now stuck in a loop of references I already visited!That probably means the litterature on the subject is not (yet) extended but I might probably be missing something.The keywords make it difficult to search : "optimisation", "algorithms", "architecture", send me most of the time to computational engineering and deep mathematics papers I unfortunately do not have the background knowledge to comprehend ! So there it is ! If you have any clue of where (or how ! ) I should be looking, please tell me :)I know Mr Rutten is pretty active on the forum so hopefully... (fingers crossed :p) !Also if you have any good tips for getting into algorithms in general (you think could help), I'd be glad to hear(read) it ! A book, tutorials maybe ?!So, autors, architects, projects books, articles, conferences I should go to,specialized architecture offices/studios (I'm also looking for an internship so ...).If you know about a more appropriate forum please let me know !If you want to get deeper into this, you can contact me at :
e1635331@student.tuwien.ac.at
tdissaux@student.ulg.ac.be
My master thesis is due for may 2018 but I have a paper to write for January 2018 in order to be elligible for a PHD program afterwards.What I mean by that is that if you read this message in 6 month, I'll still be open to discussion !
I am right now an erasmus student at TUWien (Vienna) but my main university is The university of Liège in Belgium.I can handle French, English, Italian litterature and eventually Dutch if really you think it's worth it ! I have access to most online libraries via my university's portals so access shouldn't be an issue !I'm very excited to hear from you I wish you all a great day,Cheers,Thomas
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lly it should not make much of a difference - random number generation is not affected, mutation also is not. crossover is a bit more tricky, I use Simulated Binary Crossover (SBX-20) which was introduced already in 1194:
Deb K., Agrawal R. B.: Simulated Binary Crossover for Continuous Search Space, inIITK/ME/SMD-94027, Convenor, Technical Reports, Indian Institue of Technology, Kanpur, India,November 1994
Abst ract. The success of binary-coded gene t ic algorithms (GA s) inproblems having discrete sear ch sp ace largely depends on the codingused to represent the prob lem variables and on the crossover ope ratorthat propagates buildin g blocks from pare nt strings to childrenst rings . In solving optimization problems having continuous searchspace, binary-co ded GAs discr et ize the search space by using a codingof the problem var iables in binary st rings. However , t he coding of realvaluedvari ables in finit e-length st rings causes a number of difficulties:inability to achieve arbit rary pr ecision in the obtained solution , fixedmapping of problem var iab les, inh eren t Hamming cliff problem associatedwit h binary coding, and processing of Holland 's schemata incont inuous search space. Although a number of real-coded GAs aredevelop ed to solve optimization problems having a cont inuous searchspace, the search powers of these crossover operators are not adequate .In t his paper , t he search power of a crossover operator is defined int erms of the probability of creating an arbitrary child solut ion froma given pair of parent solutions . Motivated by t he success of binarycodedGAs in discret e search space problems , we develop a real-codedcrossover (which we call the simulated binar y crossover , or SBX) operatorwhose search power is similar to that of the single-point crossoverused in binary-coded GAs . Simulation results on a number of realvaluedt est problems of varying difficulty and dimensionality suggestt hat the real-cod ed GAs with t he SBX operator ar e ab le to perform asgood or bet t er than binary-cod ed GAs wit h t he single-po int crossover.SBX is found to be particularly useful in problems having mult ip le optimalsolutions with a narrow global basin an d in prob lems where thelower and upper bo unds of the global optimum are not known a priori.Further , a simulation on a two-var iable blocked function showsthat the real-coded GA with SBX work s as suggested by Goldberg
and in most cases t he performance of real-coded GA with SBX is similarto that of binary GAs with a single-point crossover. Based onth ese encouraging results, this paper suggests a number of extensionsto the present study.
7. ConclusionsIn this paper, a real-coded crossover operator has been develop ed bas ed ont he search characte rist ics of a single-point crossover used in binary -codedGAs. In ord er to define the search power of a crossover operator, a spreadfactor has been introduced as the ratio of the absolute differences of thechildren points to that of the parent points. Thereaft er , the probabilityof creat ing a child point for two given parent points has been derived forthe single-point crossover. Motivat ed by the success of binary-coded GAsin problems wit h discrete sear ch space, a simul ated bin ary crossover (SBX)operator has been develop ed to solve problems having cont inuous searchspace. The SBX operator has search power similar to that of the single-po intcrossover.On a number of t est fun ctions, including De Jong's five te st fun ct ions, ithas been found that real-coded GAs with the SBX operator can overcome anumb er of difficult ies inherent with binary-coded GAs in solving cont inuoussearch space problems-Hamming cliff problem, arbitrary pr ecision problem,and fixed mapped coding problem. In the comparison of real-coded GAs wit ha SBX operator and binary-coded GAs with a single-point crossover ope rat or ,it has been observed that the performance of the former is better than thelatt er on continuous functions and the performance of the former is similarto the lat ter in solving discret e and difficult functions. In comparison withanother real-coded crossover operator (i.e. , BLX-0 .5) suggested elsewhere ,SBX performs better in difficult test functions. It has also been observedthat SBX is particularly useful in problems where the bounds of the optimum
point is not known a priori and wher e there are multi ple optima, of whichone is global.Real-coded GAs wit h t he SBX op erator have also been tried in solvinga two-variab le blocked function (the concept of blocked fun ctions was introducedin [10]). Blocked fun ct ions are difficult for real-coded GAs , becauselocal optimal points block t he progress of search to continue towards t heglobal optimal point . The simulat ion results on t he two-var iable blockedfunction have shown that in most occasions , the sea rch proceeds the way aspr edicted in [10]. Most importantly, it has been observed that the real-codedGAs wit h SBX work similar to that of t he binary-coded GAs wit h single-pointcrossover in overcoming t he barrier of the local peaks and converging to t heglobal bas in. However , it is premature to conclude whether real-coded GAswit h SBX op erator can overcome t he local barriers in higher-dimensionalblocked fun ct ions.These results are encour aging and suggest avenues for further research.Because the SBX ope rat or uses a probability distribut ion for choosing a childpo int , the real-coded GAs wit h SBX are one st ep ahead of the binary-codedGAs in te rms of ach ieving a convergence proof for GAs. With a direct probabilist ic relationship between children and parent points used in t his paper,cues from t he clas sical stochast ic optimization methods can be borrowed toachieve a convergence proof of GAs , or a much closer tie between the classicaloptimization methods and GAs is on t he horizon.
In short, according to the authors my SBX operator using real gene values is as good as older ones specially designed for discrete searches, and better in continuous searches. SBX as far as i know meanwhile is a standard general crossover operator.
But:
- there might be better ones out there i just havent seen yet. please tell me.
- besides tournament selection and mutation, crossover is just one part of the breeding pipeline. also there is the elite management for MOEA which is AT LEAST as important as the breeding itself.
- depending on the problem, there are almost always better specific ways of how to code the mutation and the crossover operators. but octopus is meant to keep it general for the moment - maybe there's a way for an interface to code those things yourself..!?
2) elite size = SPEA-2 archive size, yes. the rate depends on your convergence behaviour i would say. i usually start off with at least half the size of the population, but mostly the same size (as it is hard-coded in the new version, i just realize) is big enough.
4) the non-dominated front is always put into the archive first. if the archive size is exceeded, the least important individual (the significant strategy in SPEA-2) are truncated one by one until the size is reached. if it is smaller, the fittest dominated individuals are put into the elite. the latter happens in the beginning of the run, when the front wasn't discovered well yet.
3) yes it is. this is a custom implementation i figured out myself. however i'm close to have the HypE algorithm working in the new version, which natively has got the possibility to articulate perference relations on sets of solutions.
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Introduction to Grasshopper Videos by David Rutten.
Wondering how to get started with Grasshopper? Look no further. Spend an some time with the creator of Grasshopper, David Rutten, to learn the