Evolutionary design

This paper presents an evolutionary approach to style emergence in architectural designs. Emergence is the process of making features explicit which were previously only implicit. Style is considered as a set of common characteristics of a group of designs. It is interpreted using a language model as an analogy and is represented at the genetic level. An evolutionary system based on genetic engineering is developed. It emerges style by locating the genetic structures which produce that style. Preliminary results are presented.

In diesem Paper werden die für die Brainstorming-Session des Workshops MOC 2015 angenommenen und weiterführenden Themen aufgeführt und motiviert. Die diskutierenden Experten argumentieren, dass die Forschungsarbeit im Kontext der thematisierten – sich teilweise überschneidenden und ergänzenden – Gebiete erhebliches Potenzial für die Beherrschung großer realer Herausforderungen besitzt.

 Acquisition traits are those that depend, for their evolutionary (fitness) value, on the acquisition of something that gradually accumulates during an organism’s life but is not transmitted genetically to descendants. This situation causes these traits, including language, immunity, intelligence, and social status, to represent a special need for evolvability and programmed aging. Programmed aging refers to the idea that mammals and most multiparous sexually reproducing organisms evolved complex biological mechanisms that cause gradually increasing fitness deterioration and internally limit individual organism lifetimes. The rationale is that this process enhances the survival (non-extinction) of a species population. Evolvability theories propose that animals have evolved design characteristics that aid their ability to evolve, reducing the time required for a particular increment of evolutionary adaptation and/or increasing the precision with which the adaptation can be performed. Because an increase in evolvability aids a population in escaping extinction, evolution selects the associated design characteristics. Both concepts conflict with traditional (Darwinian) theory regarding details of the nature of evolution. However, more recent genetics discoveries have provided rich detail regarding the nature of the evolution process, including the fact that biological inheritance involves the transmission of organism design information from parent to descendant in digital form. These discoveries have acted to support both programmed aging and evolvability theories.

The ever-increasing availability of new types of devices raises a number of issues for user interface designers and interactive software developers. We have designed and developed a model-based authoring environment (TERESA), which provides support when designing and developing interfaces accessible through various device types in Web-based environment.

The "ZIP" adaptive automated trading algorithm has been demonstrated to outperform human traders in experimental studies of continuous double auction (CDA) markets populated by mixtures of human and "software robot" traders. Previous papers have shown that values of the eight parameters governing behavior of ZIP traders can be automatically optimized using a genetic algorithm (GA), and that markets populated by GA-optimized traders perform better than those populated by ZIP traders with manually-set parameter values. This paper introduces a more sophisticated version of the ZIP algorithm, called "ZIP60", which requires the values of 60 parameters to be set correctly. ZIP60 is shown here to produce significantly better results in comparison to the original ZIP algorithm (called "ZIP8" hereafter) when a GA is used to search the 60-dimensional parameter space. It is also demonstrated here that this works best when the GA itself has control over the dimensionality of the search-space, allowing evolution to guide the expansion of the search-space up from 8 parameters to 60 via intermediate steps. Principal component analysis of the best evolved ZIP60 parameter-sets establishes that no ZIP8 solutions are embedded in the 60-dimensional space. Moreover, some of the results and analysis presented here cast doubt on previously-published ZIP8 results concerning the evolution of new 'hybrid' auction mechanisms that appeared to be improvements on the CDA: it now seems likely that those results were actually consequences of the relative lack of sophistication in the original ZIP8 algorithm, because "hybrid" mechanisms occur much less frequently when ZIP60s are used.

This paper describes the use of a genetic algorithm (GA) to find optimal parametervalues for trading agents that operate in virtual online auction "e-marketplaces", where the rules of those marketplaces are also under simultaneous control of the GA. The aim is to use the GA to automatically design new mechanisms for agent-based e-marketplaces that are more efficient than online markets designed by (or populated by) humans. The space of possible auction-types explored by the GA includes the Continuous Double Auction (CDA) mechanism (as used in most of the world's financial exchanges), and also two purely one-sided mechanisms. Surprisingly, the GA did not always settle on the CDA as an optimum. Instead, novel hybrid auction mechanisms were evolved, which are unlike any existing market mechanisms. In this paper we show that, when the market supply and demand schedules undergo sudden "shock" changes partway through the evaluation process, two-sided hybrid market mechanisms can evolve which may be unlike any human-designed auction and yet may also be significantly more efficient than any human designed market mechanism.

algorithmic trading, online auction marketplaces, emarketplaces, automated market mechanism design, trader-agents, ZIP traders, genetic algorithms The Zero-Intelligence Plus ("ZIP") adaptive automated trading algorithm has been demonstrated to outperform human traders in experimental studies of continuous double auction (CDA) markets populated by mixtures of human and "robot" traders . To successfully populate a market with ZIP traders, the values of eight control parameters need to be set correctly. While these eight values can be set manually, previous papers have demonstrated that values of those parameters can be automatically optimized using a genetic algorithm (GA), to tailor ZIP traders to particular markets, and also (by adding an additional real-valued numeric parameter) to automatically discover novel new forms of auction market mechanism that are more efficient than the CDA. This paper introduces a more sophisticated version of the ZIP algorithm, which is shown to produce significantly better results. The extended variant is known as "ZIP60", because it requires 60 real-valued control parameters to be set correctly, and the original ZIP algorithm is re-named "ZIP8" accordingly. Manually choosing the correct values for 60 control parameters would be a very laborious task, but it is demonstrated here that an appropriate automatic optimization process can discover good sets of values for the parameters. A simple GA operating in the 60dimensional parameter space is shown to produce ZIP60 traders with mean scores significantly improved over ZIP8s, but also with high variance in those improvements. A slight revision of this approach is shown to give results with even higher mean improvements and also with lower variance in those improvements. The revised approach involves giving the GA control over the dimensionality of the parameter space being searched, starting with an eight-dimensional space and then allowing the GA to automatically and gradually expand that space up to sixtydimensional only when the increased number of parameters leads to identifiably better solutions. The results from ZIP60, while better than ZIP8, show a greatly reduced incidence of cases where the GA discovers auction mechanisms that are significantly better than the fixed CDA mechanism. This may be interpretable as evidence that the earlier ZIP8 results (where improvements on the CDA were common) were consequences of the relative lack of sophistication in the ZIP8 algorithm.

The "ZIP" adaptive automated trading algorithm has been demonstrated to outperform human traders in experimental studies of continuous double auction (CDA) markets populated by mixtures of human and "software robot" traders. Previous papers have shown that values of the eight parameters governing behavior of ZIP traders can be automatically optimized using a genetic algorithm (GA), and that markets populated by GA-optimized traders perform better than those populated by ZIP traders with manually-set parameter values. This paper introduces a more sophisticated version of the ZIP algorithm, called "ZIP60", which requires the values of 60 parameters to be set correctly. ZIP60 is shown here to produce significantly better results in comparison to the original ZIP algorithm (called "ZIP8" hereafter) when a GA is used to search the 60-dimensional parameter space. It is also demonstrated here that this works best when the GA itself has control over the dimensionality of the search-space, allowing evolution to guide the expansion of the search-space up from 8 parameters to 60 via intermediate steps. Principal component analysis of the best evolved ZIP60 parameter-sets establishes that no ZIP8 solutions are embedded in the 60-dimensional space. Moreover, some of the results and analysis presented here cast doubt on previously-published ZIP8 results concerning the evolution of new 'hybrid' auction mechanisms that appeared to be improvements on the CDA: it now seems likely that those results were actually consequences of the relative lack of sophistication in the original ZIP8 algorithm, because "hybrid" mechanisms occur much less frequently when ZIP60s are used.

This paper describes the use of a genetic algorithm (GA) to find optimal parameter-values for trading agents that operate in virtual online auction "e-marketplaces", where the rules of those marketplaces are also under simultaneous control of the GA. The aim is to use the GA to automatically design new mechanisms for agent-based e-marketplaces that are more efficient than online markets designed by (or populated by) humans. The space of possible auction-types explored by the GA includes the Continuous Double Auction (CDA) mechanism (as used in most of the world's financial exchanges), and also two purely one-sided mechanisms. Surprisingly, the GA did not always settle on the CDA as an optimum. Instead, novel hybrid auction mechanisms were evolved, which are unlike any existing market mechanisms. In this paper we show that, when the market supply and demand schedules undergo sudden "shock" changes partway through the evaluation process, two-sided hybrid market mechanisms can evolve which may be unlike any human-designed auction and yet may also be significantly more efficient than any human designed market mechanism.

The vision, ideas, observations and recommendations presented in this report are summarized from discussions by the participants during the 'Sustain What?' workshop held in New York in November 2010. The atmosphere was an example of creative collaboration at its best and the intellectual property herein belongs to the participants as a whole. Agreement with everything in the report by any single author should not be assumed as there was lively debate and disagreements over details. That said, most major points including, importantly, the feasibility of a 50-year species inventory were agreed to by all. The participants willingly set aside minor divergences of opinion in the interest of community-building and the creation of a powerful general vision for what can be.

The optimum planar antenna design utilizing a simulation tool based an integration of IE3D commercial code as an electromagnetic computational engine and an add-on optimization algorithm is proposed in this paper. The work is motivated by the popularity of planar antennas and the need of customized designs in industrial applications, which can be effectively achieved by using simulation tools. Currently available commercial codes are reliable and relatively accurate in the analysis with more efforts tending to enhance the efficiency. The quality of the antenna design will mainly rely on an effective optimization algorithm that can be and should be developed independently according to engineers' own need since the variables and cost functions for optimization can be flexibly selected. The integration of existing analysis codes, as mentioned above, and self-developed algorithms will be most effective for an engineer in the customized antenna design. The concepts and strategies are addressed with numerical examples to validate.

The main purpose of this paper is to predict the insitu compressive strength of concrete by means of non-destructive approach using ultrasonic pulse velocity (UPV) method. For this purpose generalized GMDH-type (group method of data handling) neural network was developed based on various data obtained experimentally. Evolutionary algorithms (EAs) are deployed for optimal design of GMDH-type neural networks. A set of experimental data for the training and testing the evolved GMDH-type neural network is employed in which ultrasonic pulse velocity (UPV), concrete age, water-cement ratio and fine/ coarse aggregate ratio are considered as inputs and concrete compressive strength is regarded as the output variables. Sensitivity analysis has also been carried out on one of the obtaining models to study the influence of input parameters on model output. The results show that generalized GMDH-type neural network has a great ability as a feasible tool for prediction of the concrete compressive strength.

Synthetic genetic circuits are artificial networks of transcriptional control elements inserted into living cells in order to 'program' cellular behavior. We can extend this application to programming population behavior by incorporating cell-cell communications capabilities. By designing and building such networks, cellular circuit engineers expect to gain insight into how natural genetic networks function with remarkable robustness, stability, and adaptability to changing environments. Programmed cells also have promising applications in biotechnology and medicine. A major challenge that biological circuit engineers face is the difficulty of predicting circuit performance at the design stage, with the consequence that actual construction requires significant experimental effort, even for very simple circuits. To address this fundamental obstacle we propose the use of laboratory evolution methods to create new circuit components and optimize circuit performance inside livin...

In case-based design, the adaptation of a design case to new design requirements plays an important role. If it is sufficient to adapt a predefined set of design parameters, the task is easily automated. If, however, more far-reaching, creative changes are required, current systems provide only limited success. This paper describes an approach to creative design adaptation based on the notion of creativity as 'goal oriented shift of focus of a search process'. An evolving representation is used to restructure the search space so that designs similar to the example case lie in the focus of the search. This focus is than used as a starting point to generate new designs.

This paper presents experimental results of fast intrinsic evolutionary design and evolutionary fault recovery of a 4-bit Digital to Analog Converter PAC) using the JPL stand-alone board-level evolvable system (SABLES). SABLES is part of an elport to achieve integrated evolvable systems and provides autonomous, fast (tens to hundreds of seconak), on-chp evolution involving about 100.000 circuit evaluations. Its main components are a JPL Field Programmable Tronsistor Array (FPTA) chip used ar transistor-level recontgurable hardware, and a TI DSP that implements the evolutionary algorithm controlling the FPTA reconfiguration. The paper describes an experiment consisting of the hierarchical evolution of a 4-bit DAC using 20 cells of the FPTA chip. Fault-recovery is demonstrated aper applying stuck-at 0 faults to all switches of one particular cell, and using evolution to recoverfunctionality. It has been veri$ed that thefunctionality can be recovered in less than one minute aBer the fmlt is detected while the evolutionary design of the 4-bit DACfrom scratch took about 3 minutes. ' lLSB =Vrefl16, forVref=453mV.

This paper details a simple experiment that tests two genetic encodings, NEAT and HyperNEAT, for the evolution of vision-based food-seeking behavior in neural-controlled 3D soft voxel robots. The evolution of food-seeking behavior is a preliminary step towards ecosystems of advanced artificial animals, in which the animals seek both food and mates. Two environments were tested: with and without deadly obstacles. Traditional evolutionary search was used, with an objectivebased fitness function. Both NEAT and HyperNEAT encodings were tested for the evolution of robot neural controllers. The results of the experiment showed the NEAT encoding resulted in increasingly effective food-seeking behavior over time, whereas experiments with the HyperNEAT encoding did not achieve the desired behavior. This suggests that NEAT at least is a viable algorithm to evolve neural networks for the task of vision-based object-seeking in complex robots, and warrants further experimentation. On the other hand, HyperNEAT struggled with this task. This could be due to a number of reasons, including a common issue like EA being stuck in local optima, or because the encoding might struggle to evolve and represent irregular structures required for the task.

There are many applications in aeronautics where there exist strong couplings between disciplines. One practical example is within the context of Unmanned Aerial Vehicle (UAV) automation where there exists strong coupling between operation constraints, aerodynamics, vehicle dynamics, mission and path planning. UAV path planning can be done either online or offline. The current state of path planning optimisation online UAVs with high performance computation is not at the same level as its ground-based offline optimizer's counterpart, this is mainly due to the volume, power and weight limitations on the UAV; some small UAVs do not have the computational power needed for some optimisation and path planning task. In this paper, we describe an optimisation method which can be applied to Multi-disciplinary Design Optimisation problems and UAV path planning problems. Hardware-based design optimisation techniques are used. The power and physical limitations of UAV, which may not be a problem in PC-based solutions, can be approached by utilizing a Field Programmable Gate Array (FPGA) as an algorithm accelerator. The inevitable latency produced by the iterative process of an Evolutionary Algorithm (EA) is concealed by exploiting the parallelism component within the dataflow paradigm of the EA on an FPGA architecture. Results compare software PC-based solutions and the hardware-based solutions for benchmark mathematical problems as well as a simple real world engineering problem. Results also indicate the practicality of the method which can be used for more complex single and multi-objective coupled problems in aeronautical applications.

Softwarevisualisierung und Algorithmenanimation sind wichtige Hilfsmittel der Informatikausbildung. Daher schlagen wir eine Interaktionsunterstützung zur aktiven Steuerung der Algorithmen mittels adaptiver Concept Keyboards vor. Aus dem Quelltext der Standardalgorithmen können Studierende Tastaturen frei erzeugen und konfigurieren, Methoden ausführen und so die Datenstrukturen selbst gesteuert explorieren. Zum Vergleich wird ein einfaches Schrittinterface angeboten. Nach der Evaluation ist ein vorlesungsbegleitender Einsatz geplant.

The dynamic behavior of mutation and crossover is investigated with the Breeder Genetic Algorithm. The main emphasis is on binary functions. The genetic operators are compared near their optimal performance. It is shown that mutation is most e cient in small populations. Crossover critically depends on the size of the population. Mutation is the more robust search operator. But the BGA combines the two operators in such a w ay that the performance is better than that of a single operator. For the DECEPTION function it is shown that increasing the size of the population above a certain number decreases the quality of the solutions obtained.

The FLUID approach to model-based user interface development integrates "classical" model-based approaches with software engineering concepts. In particular, FLUID models are explicitly designated to analysis or design activities and are suitably combined with analysis and design models known from object-oriented software engineering. In this paper we discuss requirements for an appropriate tool support which particularly includes support for flexible work processes with automatic as well as manual steps. With a focus on requirements analysis we sketch scenarios of model development and illustrate these topics with the FLUID tool set.

Transformational creativity requires a change of the search space. As such, Evolutionary Computation (EC) approaches are incapable of transformational creativity. In this paper, we discuss how canonical EC techniques can be extended in order to yield the potential of transformational creativity. We present a formalized description of how this can be attained, and the experimental results achieved with a metaevolutionary scheme.

An einem Teil der Topologie architektonischer Räume, dem Volumenadjazenzgraphen (VAG), wird gezeigt wie topologisches Modellieren Anwendungen der Bauplanung integrieren kann. Dazu wird ein Prototyp vorgestellt, der im wesentlichen aus drei Komponenten besteht: Mit dem Anforderungsmanager werden Anforderungen eigegeben, die formal gut handhabbar sind. Mit dem Topologiemanager werden diese Anforderungen mit gezeichneten Räumen kombiniert. Die topologischen Relationen in den Zeichnungen werden mit den entsprechenden Funktionen des GIS ermittelt und in eine Datenbank exportiert. Der Anforderungsprüfer vergleicht dann die Anforderungsdaten, die mit Hilfe des Anforderungsmanagers erzeugt wurden, mit den Topologiedaten. Dieser Ansatz soll zeigen, wie topologische Modelle eine Formalisierung semantisch hochstehender Informationen als Eigenschaften von Graphen bzw. topologischen Komplexen ermöglichen.

This paper reflects on the design and optimization of patch antennas. Two different methods were conducted. First, optimization was carried out over the whole antenna extension. Second, half antenna was optimized, and the final design was obtaining by reflection. The optimization process was conducted using genetic algorithm, return loss was obtained with full wave finite-differences time-domain, and the initial configuration (design) was obtained with line transmission and cavite method. All methods implemented in-house software. The antennas were designed to operate in Ku band with the center frequency at 16 GHz. Antenna with return greater than 22 dB and bandwidth between 2-5 GHz were obtained. The effectiveness of the proposed designs was confirmed through proper simulation results. Such optimization would aim to make a communication system more robust to electronic warfare attacks.

A case-based reasoning (CBR) knowledge base has been incorporated into a Micro-Electro-Mechanical Systems (MEMS) design tool that uses a multi-objective genetic algorithm (MOGA) to synthesize and optimize conceptual designs. CBR utilizes previously successful MEMS designs and sub-assemblies as building blocks stored in an indexed case library, which serves as the knowledge base for the synthesis process. Designs in the case library are represented in a parameterized object-oriented format, incorporating MEMS domain knowledge into the design synthesis loop as well as restrictions for the genetic operations of mutation and crossover for MOGA optimization. Reasoning tools locate cases in the design library with solved problems similar to the current design problem and suggest promising conceptual designs which have the potential to be starting design populations for a MOGA evolutionary optimization process, to further generate more MEMS designs concepts. Surface micro-machined resonators are used as an example to introduce this integrated MEMS design synthesis process. The results of testing on resonator case studies demonstrate how the combination of CBR and MOGA synthesis tools can help increase the number of optimal design concepts presented to MEMS designers.

Intelligent Agents have originated a lot of discussion about what they are, and how they are different from general programs. We describe in this paper a new paradigm for intelligent agents. This paradigm helped us deal with failures in an independent and efficient way. We proposed three types of agents to treat the system in a hierarchical way. A new way to visualize fault tolerant systems (FTS) is proposed, with the incorporation of intelligent agents, as they grow and specialize create the Multi-Agent System (MAS). The MAS contains a diversified range of agents, which depending on the perspective will be specialized or evolutionary (from our initially proposal) they will be specialized for the detection and possible solution of errors that appear in an FTS). The initial structure of the agent is proposed in [1] and named reflected agent with an internal state and in the Method MeCSMA [2]. The present work is based on the idea that with the help of the paradigm of intelligent agents, we may be able to handle fault tolerant systems, in the modality of embedded systems. The idea is to detect errors and to try to correct the failures that could happen in industrial control by monitoring and diagnosis.

In the realm of architectural design, the challenges faced are often 'wicked' in nature—complex, interconnected, and resistant to straightforward solutions. However, the emergence of genetic algorithms (GAs) has provided architects with a powerful tool to navigate these intricate problems. By emulating the principles of natural evolution, GAs enable designers to explore vast design spaces, optimize building performance, and discover innovative solutions that push the boundaries of traditional approaches.

The integration of GAs with shape grammars, as exemplified by Orestes Chouchoulas' Shape Evolution tool, demonstrates the transformative potential of this synergy. By encoding design languages into modifiable strings, architects can efficiently generate and evaluate diverse design solutions that adhere to both stylistic and functional requirements. This approach not only streamlines the design process but also facilitates the emergence of novel forms that may not have been conceived through conventional methods.

As we look towards the future, it is clear that the application of genetic algorithms in architecture is poised for significant growth. With the increasing complexity of design challenges and the rapid advancement of computational technologies, GAs will undoubtedly play a pivotal role in shaping the built environment. However, it is crucial to recognize that the successful implementation of these algorithms requires a deep understanding of both architectural principles and computational techniques.

Ultimately, the power of genetic algorithms lies not in their ability to replace human creativity but rather in their capacity to augment it. By leveraging the strengths of both human intuition and computational optimization, architects can unlock new realms of possibility and create designs that are not only functional and aesthetically pleasing but also responsive to the ever-changing needs of society. As we embrace this symbiotic relationship between human ingenuity and algorithmic innovation, we can look forward to a future where the 'wicked' problems of architectural design are met with equally 'wicked' solutions.

This paper investigates the engineering development as an evolutionary process. Therefore it first reveals the benefits of evolutionary algorithms in engineering and considers the evolutionary design. Next it brings a simple analytical model of a common ship hull subjected to service conditions. Finally the optimization in the ship structural design is considered as an evolutionary process tackled by NSGA-II algorithm that is applied in backtracing of the ship scantling development. The conclusion is that the history of technical development can support comprehension of the role of environment, knowledge, material properties and workmanship in engineering regarding safety, efficiency and manufacturing.

Terrain generation algorithms have an important role in video games: they can provide a realistic scenario for the game experience, or can help keep the user interested in playing by providing new landscapes each time he plays. Nowadays there are a wide range of techniques for terrain generation, but all of them are focused on providing realistic terrains, often neglecting other aspects (e.g., aesthetic appeal or presence of desired features). This paper proposes a new technique, Genetic Terrain Programming, based on evolutionary design with GP to allow game designers to evolve terrains accordingly to their aesthetic feelings or desired features. The developed application produces Terrains Programs (TPs) that will always generate different terrains, but consistently with the same features (e.g. valleys, lakes). This characteristic will allow game designers to endow games with programs capable of generating different coherent landscapes each time users run the game.

Cell fate is programmed through gene regulatory networks that perform several calculations to take the appropriate decision. In silico evolutionary optimization mimics the way Nature has designed such gene regulatory networks. In this review we discuss the basic principles of these evolutionary approaches and how they can be applied to engineer synthetic networks. We summarize the basic guidelines to implement an in silico evolutionary design method, the operators for mutation and selection that iteratively drive the network architecture towards a specified dynamical behavior. Interestingly, as it happens in natural evolution, we show the existence of patterns of punctuated evolution. In addition, we highlight several examples of models that have been designed using automated procedures, together with different objective functions to select for the proper behavior. Finally, we briefly discuss the modular designability of gene regulatory networks and its potential application in biotechnology.

I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work.

Convolution and multiplication operations in the filtering process can be optimized by minimizing the resource utilization using Field Programmable Gate Arrays (FPGA) and separable filter kernels. An FPGA architecture for separable convolution is proposed to achieve reduction of on-chip resource utilization and external memory bandwidth for a given processing rate of the convolution unit. Multiplication in integer number system can be optimized in terms of resources, operation time and power consumption by converting to logarithmic domain. To achieve this, a method altering the filter weights is proposed and implemented for error reduction. The results obtained depict significant error reduction when compared to existing methods, thereby optimizing the multiplication in terms of the above mentioned metrics. Underwater video and still images are used by many programs within National Oceanic Atmospheric and Administration (NOAA) fisheries with the objective of identifying, classifying and quantifying living marine resources. They use underwater cameras to get video recording data for manual analysis. This process of manual analysis is labour intensive, time consuming and error prone. An efficient solution for this problem is proposed which uses Gabor filters for feature extraction. The proposed method is implemented to identify two species of fish namely Epinephelus morio and Ocyurus chrysurus. The results show higher rate of detection with minimal rate of false alarms.

Convolution and multiplication operations in the filtering process can be optimized by minimizing the resource utilization using Field Programmable Gate Arrays (FPGA) and separable filter kernels. An FPGA architecture for separable convolution is proposed to achieve reduction of on-chip resource utilization and external memory bandwidth for a given processing rate of the convolution unit. Multiplication in integer number system can be optimized in terms of resources, operation time and power consumption by converting to logarithmic domain. To achieve this, a method altering the filter weights is proposed and implemented for error reduction. The results obtained depict significant error reduction when compared to existing methods, thereby optimizing the multiplication in terms of the above mentioned metrics. Underwater video and still images are used by many programs within National Oceanic Atmospheric and Administration (NOAA) fisheries with the objective of identifying, classifying and quantifying living marine resources. They use underwater cameras to get video recording data for manual analysis. This process of manual analysis is labour intensive, time consuming and error prone. An efficient solution for this problem is proposed which uses Gabor filters for feature extraction. The proposed method is implemented to identify two species of fish namely Epinephelus morio and Ocyurus chrysurus. The results show higher rate of detection with minimal rate of false alarms.

The ability of an organism to survive depends on its capability to adapt to external conditions. In addition to metabolic versatility and efficient replication, reliable signal transduction is essential. As signaling systems are under permanent evolutionary pressure one may assume that their structure reflects certain functional properties. However, despite promising theoretical studies in recent years, the selective forces which shape signaling network topologies in general remain unclear. Here, we propose prevention of autoactivation as one possible evolutionary design principle. A generic framework for continuous kinetic models is used to derive topological implications of demanding a dynamically stable ground state in signaling systems. To this end graph theoretical methods are applied. The index of the underlying digraph is shown to be a key topological property which determines the so-called kinetic ground state (or off-state) robustness. The kinetic robustness depends solely on the composition of the subdigraph with the strongly connected components, which comprise all positive feedbacks in the network. The component with the highest index in the feedback family is shown to dominate the kinetic robustness of the whole network, whereas relative size and girth of these motifs are emphasized as important determinants of the component index. Moreover, depending on topological features, the maintenance of robustness differs when networks are faced with structural perturbations. This structural off-state robustness, defined as the average kinetic robustness of a network's neighborhood, turns out to be useful since some structural features are neutral towards kinetic robustness, but show up to be supporting against structural perturbations. Among these are a low connectivity, a high divergence and a low path sum. All results are tested against real signaling networks obtained from databases. The analysis suggests that ground state robustness may serve as a rationale for some structural peculiarities found in intracellular signaling networks.

In pattern classification problems, many works have been carried out with the aim of designing good classifiers from different perspectives. These works achieve very good results in many domains. However, in general they are very dependent on some crucial parameters involved in the design. These parameters have to be found by a trial and error process or by some automatic methods, like heuristic search and genetic algorithms, that strongly decrease the performance of the method. For instance, in nearest prototype approaches, main parameters are the number of prototypes to use, the initial set, and a smoothing parameter. In this work, an evolutionary approach based on Nearest Prototype Classifier (ENPC) is introduced where no parameters are involved, thus overcoming all the problems that classical methods have in tuning and searching for the appropiate values. The algorithm is based on the evolution of a set of prototypes that can execute several operators in order to increase their quality in a local sense, and with a high classification accuracy emerging for the whole classifier. This new approach has been tested using four different classical domains, including such artificial distributions as spiral and uniform distibuted data sets, the Iris Data Set and an application domain about diabetes. In all the cases, the experiments show successfull results, not only in the classification accuracy, but also in the number and distribution of the prototypes achieved.

Frau Petzold danke ich sehr für die orthographische Durchsicht der vorliegenden Arbeit. Meiner Lebensgefährtin Katharina Richter für die unzähligen abendlichen Diskussionen über Architektur und Forschung. Mein größter Dank aber gilt meinen Eltern, die meine Wege und Ziele immer unterstützten. Thesen Grundlagen These 1 Der ungenutzte Gebäudebestand in der Bundesrepublik Deutschland deckt zum größten Teil den Bedarf an Wohn-und Arbeitsraum. Deshalb liegt die planerische Herausforderung im Umbau und in der Umnutzung dieser Gebäude. These 2 Umbau und Umnutzung sind Strategien zur Erhaltung existenter Werte. Aus diesem Grund müssen ungenutzte Bestandsgebäude einer Weiternutzung zugeführt werden. These 3 Das Ziel jeder Revitalisierungsmaßnahme ist die ressourcenschonende Weiternutzung des Gebäudebestandes. Deshalb muss die Entscheidung, ob und wie ein Gebäude revitalisiert wird, nicht nur unter ökonomischen, sondern auch unter ökologischen Gesichtspunkten getroffen werden. These 4 Die Entscheidung, ob ein Gebäude umgebaut oder umgenutzt werden kann, wird zu Beginn der Planungstätigkeit getroffen. Deshalb muss die Durchführbarkeit einer Revitalisierungsmaßnahme zu diesem Zeitpunkt plausibel dargelegt werden. Es gibt keine computergestützten Werkzeuge, die den Architekten bei der Lösung dieser Aufgabe unterstützen. Revitalisierung-Potential These 5 Der Gebäudebestand ist heterogen und nicht eindeutig typologisierbar. Dennoch kann ein Merkmal aus dem Bestand extrahiert werden, an Hand dessen nahezu jedes Gebäude kategorisiert werden kann. Dieses Merkmal ist die Konstruktion des Gebäudes. These 6 Fast jedes komplexe Gebäude kann entweder als Gebäude mit massiver Konstruktion oder als Gebäude mit leichter Konstruktion kategorisiert werden. These 7 Gebäude mit massiven Konstruktionen sind gekennzeichnet durch die schwierige Trennbarkeit von Primär-, Sekundär-und Tertiärstruktur. Ihre Grundrissorganisation ist demzufolge unflexibel und kann nur mit erheblichen Eingriffen in die Bausubstanz in größerem Umfang verändert werden. These 8 Gebäude mit leichten Konstruktionen sind gekennzeichnet durch die einfache Trennbarkeit von Primär-, Sekundär-und Tertiärstruktur. Ihre Grundrissorganisation ist demzufolge flexibel und kann mit geringen Eingriffen in die Bausubstanz in größerem Umfang verändert werden. 5 Revitalisierung-Strategien These 9 Der Umbau eines Gebäudes ist mit dem Abbruch von Bauteilen verbunden. Daher kann der Umbau als zerstörungsreiche Vorgehensweise bezeichnet werden. These 10 Die Umnutzung eines Gebäudes kann ohne den Abbruch von Bauteilen erfolgen. Daher kann die Umnutzung als zerstörungsarme Vorgehensweise bezeichnet werden. These 11 Unter der Bedingung des nachhaltigen Umgangs mit dem Gebäudebestand ist die Weiternutzung eines Gebäudes unter größtmöglicher Beibehaltung der existenten Bausubstanz und unter geringstmöglicher Veränderung des baulichen Zustands zu erreichen. Die Umnutzung eines Gebäudes kann daher als die ökologischste Revitalisierungsmaßnahme bezeichnet werden. Vor der Entscheidung für einen Umbau ist demzufolge die Durchführbarkeit einer Umnutzung oder einer Kombination aus Umnutzung und Umbau zu prüfen. These 12 Im unter ökologischen Gesichtpunkten betrachteten Idealfall des Verzichts auf bauliche Eingriffe ist es ausreichend, ein Gebäude organisatorisch zu verändern, so dass durch den Tausch von Flächen auf neue Nutzerprofile abgestimmte veränderte Nutzungseinheiten gebildet werden können. 6 Revitalisierung-Methodik These 13 Architekten verwenden unterschiedliche Methoden zur Lösung von Entwurfsproblemen. Aus diesem Grund gibt es keine allgemeingültige Vorgehensweise, die als Anhaltspunkt für die Entwicklung computergestützter Werkzeuge dienen könnte. These 14 Der Planungsprozess erfordert die Entwicklung von alternativen Lösungsmöglichkeiten einer Entwurfsaufgabe nach gleichen oder grundsätzlich verschiedenen Anforderungen. Diese Forderung kann im Fall einer Revitalisierungsmaßnahme derart komplex sein, dass ein Architekt sie nicht erfüllen kann. These 15 Das Entwerfen ist nicht frei von normativen Einflüssen. Gesetze, Verordnungen und Richtlinien müssen ebenso beachtet werden, wie gestalterische, wirtschaftliche oder technische Faktoren. Deshalb müssen normative Einflüsse als zu erfüllende Bedingungen oder Ziele betrachtet werden. These 16 Ein wesentliches Kriterium für oder gegen die Entscheidung, ein Gebäude zu revitalisieren, ist die Möglichkeit, den Ist-Zustand (Bestandsgrundriss) an den Soll-Zustand (Raumprogramm) anzupassen. Diese Anpassung stellt eine komplexe kombinatorische Problemstellung dar, deren potentieller Lösungsraum so groß ist, dass eine manuell entwickelte Lösung hinsichtlich der Existenz alternativer Lösungsmöglichkeiten nicht objektiv bewertet werden kann. 7 Modellbildung These 17 Die zerstörungsreiche Vorgehensweise beim Umbau besitzt Analogien zur Methodik der Organisation von Warenlagern oder Containerterminals, bei denen Artefakte in Form von Waren durch Sortieren, Umschichten oder Verlagern dergestalt in ihrer Position verändert werden, dass eine Zielvorgabe ("Gute Erreichbarkeit") erfüllt wird. These 18 Die zerstörungsarme Vorgehensweise bei der Umnutzung besitzt Analogien zur Methodik von Brettspielen, wie Schach, Go oder 4Gewinnt, bei denen Artefakte in Form von Feldern oder Kreuzungspunkten von Rasterlinien dergestalt mit Spielsteinen belegt werden, dass eine Zielvorgabe ("Spielgewinn") erfüllt wird. These 19 Aus der Methodik der zitierten Analogien können für die zerstörungsreiche und die zerstörungsarme Vorgehensweise Modelle abgeleitet werden, die mit Hilfe der Informationstechnologie darstellbar sind. Informationstechnologie These 20 Umbau und Umnutzung sind kombinatorische Problemstellungen. Diese lassen sich als Optimierungsprobleme darstellen und mit Methoden des Operations Research lösen. 8 Systemkonzeption These 21 Normative Einflüsse können in Optimierungsmodellen als Bedingungen definiert werden. Diese Bedingungen schränken den potentiellen Lösungsraum eines Revitalisierungsproblems ein, so dass untaugliche Lösungen vermieden werden. These 22 Entwurfsziele können in Optimierungsmodellen als Zielfunktionen definiert werden. Diese Zielfunktionen können gewichtet werden, so dass im Sinne der ressourcenschonenden Nutzung des Bestandes auch die nicht vollständige Erfüllung aller Ziele als Entscheidung für die Durchführung einer Revitalisierungsmaßnahme in Betracht gezogen werden kann. These 23 Optimierungsmodelle können die Anzahl der Lösungen für ein Revitalisierungsproblem umfassend erhöhen. These 24 In kürzerer Zeit können mit einem Optimierungsmodell mehr Lösungen eines Revitalisierungsproblems gefunden werden, als mit traditionellen Methoden. These 25 Die Performance einer mit einem Optimierungsmodell ermittelten Lösung eines Revitalisierungsproblems ist auf der Grundlage der vom Architekten aufgestellten Anforderungen objektiv messbar. These 26 Die tatsächliche Leistungsfähigkeit des Einsatzes von Optimierungsverfahren in der Revitalisierung kommt erst dann zum Tragen, wenn Umbau und Umnutzung als gleichberechtigte Alternativen zum Neubau in Betracht gezogen werden. Deshalb muss sich die Herangehensweise des Architekten an den Planungsprozess grundlegend verändern.

This paper introduces the oriented-tree network design problem (OTNDP), a general problem of tree network design with several applications in different fields. We also present several adaptations needed by evolutionary algorithms with Cayley-type encodings to tackle the OTNDP. In particular, we present these adaptations in two Cayley-encodings known as Prüfer and Dandelion codes. We include changes in Cayley-encodings to consider rooted trees. We also show how to use a fixed-length encoding for Cayley codes in evolutionary algorithms, and how to guarantee that the optimal solution is included in the search space. Finally, we present several adaptations of the evolutionary algorithm's operators to deal with Cayley-encodings for the OTNDP. In the experimental part of the paper, we compare the performance of an evolutionary algorithm (implementing the two Cayleyencodings considered) in several OTNDP instances: first, we test the proposed techniques in randomly generated instances, and second, we tackle a real application of the OTNDP: the optimal design of an interactive voice response system (IVR) in a call center.

Microstructured optical fibres are a relatively recent advance in fibre technology which guide light by using arrays of air holes which run the length of the fibre. The internal microstructure of optical fibres can be altered to reshape and transform light for use in medical applications, sensing, long distance and local area network high bandwidth communications. Recent progress in the production of polymer fibres allows designs with complex microstructures consisting of hundreds of holes to be manufactured. In this paper we present a generative (embryogenic) representation which can produce symmetric fibre designs with a variable number of holes. The resulting genetic algorithm has the ability to search designs of varying complexity over time, allowing less or more complex designs to be evolved as required. Various aspects of this representation are discussed in light of the supporting genetic algorithm such as as recombination of designs and the conversion of the variable length binary genotype to the phenotype (optical fibre structure). We include some single objective design results for a highbandwidth optical fibre along with manufactured designs.

High-Z materials are considered the best candidates for plasma facing components (PFCs) in future fusion devices, while ion cyclotron range of frequencies (ICRF) heating is a method of choice because of its flexibility, cost effectiveness, and plug-to-power efficiency. But high-Z materials and ICRF have been a difficult combination. ASDEX Upgrade (AUG) is pioneering the use of a tungsten (W) wall and in the next years it will prove (or disprove) the appropriateness of this combination for the future. This paper describes the optimization procedure for and the main features of a new proposed ICRF antenna for AUG specifically designed to improve the compatibility of ICRF with a high-Z metallic wall. The optimization criteria for a new design are based on a reduction of the parasitic parallel electric field responsible of the impurity production. The evolutionary design of the 2-strap antenna is compared with a redesigned 4-strap antenna embedded in the wall. Moreover, options and constraints on how to integrate a wider antenna in the present configuration of ASDEX Upgrade and its integration on the stabilizing wall are discussed.

An important benefit of multi-objective search is that it maintains a diverse population of candidates, which helps in deceptive problems in particular. Not all diversity is useful, however: candidates that optimize only one objective while ignoring others are rarely helpful. A recent solution is to replace the original objectives by their linear combinations, thus focusing the search on the most useful tradeoffs between objectives. To compensate for the loss of diversity, this transformation is accompanied by a selection mechanism that favors novelty. This paper improves this approach further by introducing novelty pulsation, i.e. a systematic method to alternate between novelty selection and local optimization. In the highly deceptive problem of discovering minimal sorting networks, it finds state-of-the-art solutions significantly faster than before. In fact, our method so far has established a new world record for the 20-line sorting network with 91 comparators. In the real-world problem of stock trading, it discovers solutions that generalize significantly better on unseen data. Composite Novelty Pulsation is therefore a promising approach to solving deceptive real-world problems through multi-objective optimization.

This paper describes the use of topology optimization as a synthesis tool for the design of largedisplacement compliant mechanisms. An objective function for the synthesis of large-displacement mechanisms is proposed together with a formulation for synthesis of path-generating compliant mechanisms. The responses of the compliant mechanisms are modelled using a total Lagrangian ÿnite element formulation, the sensitivity analysis is performed using the adjoint method and the optimization problem is solved using the method of moving asymptotes. Procedures to circumvent some numerical problems are discussed. Copyright ? 2001 John Wiley & Sons, Ltd.

This paper describes the use of topology optimization as a synthesis tool for the design of large‐displacement compliant mechanisms. An objective function for the synthesis of large‐displacement mechanisms is proposed together with a formulation for synthesis of path‐generating compliant mechanisms. The responses of the compliant mechanisms are modelled using a total Lagrangian finite element formulation, the sensitivity analysis is performed using the adjoint method and the optimization problem is solved using the method of moving asymptotes. Procedures to circumvent some numerical problems are discussed. Copyright © 2001 John Wiley & Sons, Ltd.

The paper describes further developments of the interactive evolutionary design concept relating to the emergence of mutually inclusive regions of high performance design solutions. These solutions are generated from cluster-oriented genetic algorithm (COGAs) output and relate to a number of objectives introduced during the preliminary design of military airframes. The datamining of multi-objective COGA (moCOGA) output further defines these regions through the application of clustering algorithms, data reduction and variable attribute relevance analyses. A number of visual representations of the COGA output projected onto both variable and objective space are presented. The multi-objective output of the COGA is compared to output from a Strength Pareto Evolutionary Algorithm (SPEA-II) to illustrate the manner in which moCOGAs can generate good approximations to Pareto frontiers.