Some caad packages offer additional support for the optimization of spatial configurations, but the possibilities for applying optimization are usually limited either by the complexity of the data model or by the constraints of the underlying caad system. Since we missed a system that allows to experiment with optimization techniques for the synthesis of spatial configurations, we developed a collection of methods over the past years. This collection is now combined in the presented open source library for computational planning synthesis, called CPlan. The aim of the library is to provide an easy to use programming framework with a flat learning curve for people with basic programming knowledge. It offers an extensible structure that allows to add new customized parts for various purposes. In this paper the existing functionality of the CPlan library is described

König, Reinhard

Koenig, Reinhard

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CPlan: An Open Source Library for Computational Analysis and Synthesis: An Open Source Library for Computational Analysis and Synthesis

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CPlanAnOpen Source Library for Computational Analysis and SynthesisReinhard Koenig11ETH Zurich1http://www.ia.arch.ethz.ch/koenig/1reinhard.koenig@arch.ethz.chSome caad packages offer additional support for the optimization of spatialconfigurations, but the possibilities for applying optimization are usually limitedeither by the complexity of the data model or by the constraints of the underlyingcaad system. Since we missed a system that allows to experiment withoptimization techniques for the synthesis of spatial configurations, we developeda collection of methods over the past years. This collection is now combined inthe presented open source library for computational planning synthesis, calledCPlan. The aim of the library is to provide an easy to use programmingframework with a flat learning curve for people with basic programmingknowledge. It offers an extensible structure that allows to add new customizedparts for various purposes. In this paper the existing functionality of the CPlanlibrary is described.Keywords: Evolutionary algorithms, Open source, Planning synthesis, C-Sharp,Spatial configurationsINTRODUCTIONTo be independent from existing CAAD packages weimplemented basic geometry objects with a com-putational geometry library as well as a geometryviewer with corresponding mouse interaction (seesection "Geometry library, viewer and mouse inter-action"). For evaluating spatial conﬁgurations weprovide a collection of computational analysis meth-ods (see section "Computational analysis"). For theautomatic generation of spatial conﬁgurations thereare various methods described in section "Genera-tivemethods". The synthesis methods of the CPlan li-brary combines everything by using single- or multi-criteria optimization methods (see section "Synthe-sis methods"). Section "Visualization" describes ourapproach for mapping a multi-dimensional solutionspace to 2D by using Self-Organizing-Maps. All partsof the CPlan library are open source and are designedthat they can be extended using the provided inter-face classes.GEOMETRY LIBRARY, VIEWER ANDMOUSE INTERACTIONThebasic component is a viewer for 2Dand3D,whichincludes the usual basic view controls like pan, zoom,and rotate. In addition there is a set of geometry ob-jects that canbe visualizedby the viewer in away thatDesign Tools - Exploration - Volume 1 - eCAADe 33 | 245the program code to add geometries is minimizedand as simple as possible. Basic mouse interactionmethods like pick, move, and rotate are already im-plemented for eachgeometry object. There are inter-faces for lines, surfaces, and bodies that allow a userto add own geometrical objects that can be visual-ized and used for mouse interaction in the same wayas the existing objects. On the project website thereare already samples for the introduction how to usethe viewer and the geometry classes with integratedmouse interaction. It is basically a very rudimentarycad system (see ﬁgure 1).Figure 1Two examples forusing the geometryobjects and theviewer. Top: Asimple 2Drectangle. Bottom:Objects in 3D view.COMPUTATIONAL ANALYSISAmore advanced part of the CPlan library covers var-ious evaluation methods for spatial conﬁgurations.So far there are graphmeasure to calculate centralitymeasures for street networks as known from SpaceSyntax (Hillier, 2007; Turner, 2001): Integration (cen-trality) andChoice (in-betweenness centrality), whichcanbe calculated for custom radii (ﬁgure 2b). We alsooﬀer the following Isovists ﬁeld calculations (Batty,2001; Benedikt, 1979; Turner, Doxa, O'Sullivan, &Penn, 2001) for the analysis of the view ﬁeld proper-ties: Area, compactness, occlusivity, perimeter, minradial,max radial (ﬁgure3bandc). Furthermore thereare visibility graph analysis (Turner et al., 2001) for theevaluation of visual centralities, and solar analysis tocalculate the shadowing or the solar exposure duringa deﬁned period of time using HDRI maps [3] (ﬁgure3d). All evaluation methods are prepared to be runon a distributed system (LUCI) that is developed forparallel evaluation of larger sets of spatial conﬁgura-tions. This is necessary for theusageof the evaluationmethods for objective functions in the context of op-timization. The LUCI middleware itself is not part ofthe CPlan library but a separate project [4].GENERATIVEMETHODSThere are generators for street networks, parceling,building layouts, and building ﬂoorplans. Figure 2ashows a street network generated with random pa-rameters using the algorithm from Koenig, Treyer,and Schmitt (2013). Figure 2b illustrates the central-ity analysis (choice) of thenetwork. Theblocks, whichare automatically generated for the street network(ﬁgure 2a) can be used for the parceling algorithmfrom Knecht and Koenig (2012). Based on the blockor parcel structure we can generate layouts for build-ing volumes (ﬁgure 3a). Figure 3b and c show Isovistanalysis and ﬁgure 3c a solar analysis for the gener-ated building layout.SYNTHESIS METHODSThe classes for evolutionary multi-criteria optimiza-tion (EMO) aremost important ones that enableplan-ning synthesis. They are also the most sophisticatedpart of the CPlan library. We have not implementednew EMOalgorithms, but used a set of well tested ex-246 | eCAADe 33 - Design Tools - Exploration - Volume 1isting ones. As blueprint for the classes for popula-tions, chromosomes, and ﬁtness functions we buildon the AForge.Net framework [2]. The classes fromthis framework are adapted for multi-criteria opti-mization. As multi-criteria selection mechanism weimplemented awrapper to thePISA selectors [5]. Thisbasic setup is applicable for any kind of optimizationproblem.Figure 2a) Generated streetnetwork withblocks, b) Networkanalysis showingthe centralitymeasure choice.Beside the evaluation algorithms we added cus-tomized algorithms for the generation of street net-works and building layouts. These generators are ei-ther directly encapsulated in a chromosome (as forthebuilding layouts) or theyuse the chromosomes asinstructions for a more complex embryogeny, whichis the mapping process from a genotype to a phe-notype. Both algorithms may serve as examples forthe implementation of own customized generatorsfor spatial conﬁgurations. The provided interfaces forchromosomes and ﬁtness functions ensure that ownalgorithms are compatible with the population andthe selectors, which can remain always the same.The last two ﬁgure show exemplary applicationsof the CPlan library for planning synthesis in two dif-ferent urban environment. Existing street networksand building geometries can be imported via dxf. Atthe top ﬁgure only building layouts are synthesized.The ﬁgure below shows a process where ﬁrst thestreet network is synthesized and second the build-ing layout for the blocks is created.VISUALIZATIONAnother important aspect for dealing with EMO isthe possibility to visualize the solution set in a mean-ingful way. Since there is usually not one best solu-tion, but a set of pareto-optimal solutions, we need amethod to show themona2Dmap. ThereforeweuseSOMs. They are able to reduce a multi-dimensionalspace to a 2D space, on which the solutions areshown in an understandable way for an urban plan-ner or an architect. To produce SOM visualizationswe have coupled the CPlan library to the DatabionicESUM tools (Ultsch & Moerchen, 2005).WOWTOUSE ITIn following we introduce the usage of the CPlan li-brary for design synthesis applications. In the frame-work of this paper we can only explain the basic con-cepts. We are continuously working to extend thedocumentation of the CPlan library and examples forits usage on the project website [1].Themain part for implementing a new optimiza-Design Tools - Exploration - Volume 1 - eCAADe 33 | 247Figure 3a) Generatedbuilding layout, b)Isovist analysisshowing the areaproperty, c) Isovistanalysis showingthe min radialproperty, d) Solaranalysis.tion problem is to create a custom chromosome,which contains all necessary information for a spa-tial conﬁguration (e.g. for a street network, a build-ing volume layout, or a ﬂoorplan). A spatial conﬁg-uration is composed out of spatial entities that arestored as gens inside a chromosome. Gens usuallyrepresent the smallest spatial entities like street seg-ments, parcels, buildings, or rooms. Gens are manip-ulated by mutation, crossover, and adaptation oper-ators on the chromosome level. All chromosomes arestored into a population class, from where all opera-tors are called per iteration (also called generation ortime step).The quality of a chromosome, respectively of avariation of a spatial conﬁguration is evaluated bya corresponding ﬁtness function. This function cancompute one (or formulti-criteria optimization prob-lems many) objective values, which shall be mini-mizedormaximizedduring theoptimizationprocess.The computational analysis methods of the CPlan li-brary are made for being used with ﬁtness functions.The structure of the optimization classes can besummarized as follows: A set of chromosomes whichrepresents design variants are stored as a list in apop-ulation. The chromosomes itself consist of a list ofgens. Each gen stores the information (e.g. param-eters) of a spatial entity (e.g. a building). In the fol-lowing we give some code examples.To create a new chromosome we inherit fromone of the base chromosomes provided by the CPlanlibrary:public class ChromosomeBuildingLayout,! : ChromosomeBaseIn the constructor of the custom chromosome usu-ally the restrictions for a spatial conﬁguration are de-ﬁned:myBuildingLayout = new,! ChromosomeBuildingLayout (,! borderPolygon, MinNrBuildings,248 | eCAADe 33 - Design Tools - Exploration - Volume 1,! MaxNrBuildings, Density,,! MinBuildingSideRatio);A custom ﬁtness function need to inherit from thecorresponding interface:public class,! FitnessFunctionBuldingLayout :,! IFitnessFunctionWe create an instance of our ﬁtness function:FitnessFunctionBuldingLayout,! myFitnessFunction = new,! FitnessFunctionBuldingLayout();And send the chromosome and the ﬁtness functionto the constructor of our population:myPopulation = new,! BuildingLayoutPopulation(,! _populationSize, alpha, lambda, mu,! , curChromosome, fitnessFunction);The population class is always the same for all pos-sible chromosomes. A generation of iteration of thepopulation is executed by:myPopulation.RunEpoch();Whereas the RunEpochmethod runs all operators onthe chromosomes:public RunEpoch( ){Crossover();Mutate();Adapt();}Like the other operators, the Adapt() method canbe implemented individually for customized chro-mosome class. We use it to ensure that a variationis valid, e.g. by a collision detection algorithm, whichavoids overlapping of buildings moved randomly bythe mutation operator. This makes the optimizationmore eﬃcient, since it do not need to test all impos-sible designs.Figure 4Software prototypeshowing the mainareas of thesynthesis systemsuser interface: a) a3D view combinesone solution out ofeach archive,design solutions ofthe archives for b)buildings layoutsand c) streetnetworks, and d)ﬁelds for the userinput of size ofpopulation, numberof generations, etc.Design Tools - Exploration - Volume 1 - eCAADe 33 | 249Figure 4b shows a population of building layouts af-ter a certain number of iterations. Whereas, the pre-cise description in the context of a multi-criteria op-timization is, that the set of solutions in ﬁgure 4bshows the archive of all best so far found layouts.Figure 3b, c, and d visualize results of possible ﬁt-ness functions. Theoretically each of the color val-ues in the ﬁgures can be used as objective value. Thismeans that we can for example deﬁne a ﬁtness func-tion, which shall maximize the area value in the mid-dle of the area of the building layouts in ﬁgure 3. Asshown by Schneider and Koenig (2012), the resultswould be, that the buildings are placed at the borderof the area after some iterations.CONCLUSIONThe CPlan open source library is an easy to use andwell extensible programming framework for compu-tational analysis and planning synthesis. It is pub-lished under the GNU Lesser General Public Licenseand available via the project website [1]. The libraryis written primarily in C-Sharp, while special parts areimplemented in managed C++.There is an active development of the library es-pecially for various application scenarios. The docu-mentation is primarily done by xlm documentationcomments directly in the source code. Samples onthe project website help for the ﬁrst steps in pro-gramming an own application. We are looking for ac-tive developers who support the project or use theframework for aapplication scenarios.ACKNOWLEDGEMENTSThe authowwant to thank the following contributorsof the CPlan library: Sven Schneider, Christian Tonn,Martin Bielik, Artem Chirkin, Christine Meixner, Dr.Bernhard Klein, Lukas Treyer, Zeng Wei, Pavol Bielik,Matthias Standfest. The complete CPlan project withall its libraries can be downloaded at www.cplan-group.net.REFERENCESBatty, M 2001, 'Exploring Isovist Fields: Space and Shapein Architectural and Urban Morphology', Environ-ment and Planning B Planning and Design, 28(1), pp.123-150Benedikt, ML 1979, 'To take hold of space: isovists andisovist ﬁelds', Environment and Planning B, 6(1), pp.47 - 65Hillier, B 2007, Space is themachine: A conﬁgurational the-ory of architecture, Space SyntaxKnecht, K and Koenig, R 2012, 'Automatische Grund-stuecksumlegung mithilfe von Unterteilungsalgo-rithmen und typenbasierte Generierung von Stadt-strukturen', Arbeitspapiere Informatik in der Architek-tur, 15(15), pp. 1-21Koenig, R and Knecht, K 2014, 'Comparing two evolu-tionary algorithmbasedmethods for layout genera-tion: Dense packing versus subdivision', Artiﬁcial In-telligence for Engineering Design, Analysis andManu-facturing, 28(03), pp. 285-299Koenig, R, Treyer, L and Schmitt, G 2013 'Graphicalsmalltalk with my optimization system for urbanplanning tasks', Proceedings of the 31st eCAADe Con-ference – Volume 2, Delft, Netherlands, pp. 195-203Schneider, S, Fischer, JR and Koenig, R 2011, 'RethinkingAutomated Layout Design: Developing a CreativeEvolutionary Design Method for the Layout Prob-lems in Architecture and Urban Design.', in Gero,JS (eds) 2011, Design Computing and Cognition ’10,Springer Netherlands, Stuttgart, pp. 367-386Schneider, S and Koenig, R 2012 'Exploring the Gen-erative Potential of Isovist Fields: The EvolutionaryGeneration of Urban Layouts based on Isovist FieldProperties', 30th International Conference on Educa-tion and research in Computer Aided Architectural De-sign in Europe, Prague, pp. 355-363Turner, A 2001 'Angular Analysis', 3rd International SpaceSyntax Symposium, AtlantaTurner, A, Doxa, M, O'Sullivan, D and Penn, A 2001,'From isovists to visibility graphs: amethodology forthe analysis of architectural space', Environment andPlanning B: Planning and Design, 28(1), pp. 103-121Ultsch, A and Moerchen, F 2005, 'ESOM-Maps: toolsfor clustering, visualization, and classiﬁcation withEmergent SOM', Dept. of Mathematics and ComputerScience, University of Marburg, pp. 1-7[1] http://cplan-group.net[2] http://www.aforgenet.com/framework[3] http://freac-x.de/freac/drupal/?q=download/hdri_sky_generator[4] https://bitbucket.org/treyerl/lucy[5] http://www.tik.ee.ethz.ch/sop/pisa/250 | eCAADe 33 - Design Tools - Exploration - Volume 1

CPlan: An Open Source Library for Computational Analysis and Synthesis

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