Improving Design Optimization and Optimization-based Design Knowledge Discovery

The use of design optimization in the early stages of architectural design process has attracted a high volume of research in recent years. However, traditional design optimization requires a significant amount of computing time, especially when there are multiple design objectives to achieve. What’s more, there is a lack of studies in the current research on automatic generation of architectural design knowledge from optimization results. This paper presents computational methods for creating and improving a closed loop of design optimization and knowledge discovery in architecture. It first introduces a design knowledge-assisted optimization improvement method with the techniques - offline simulation and Divide & Conquer (D&C) - to reduce the computing time and improve the efficiency of the design optimization process utilizing architectural domain knowledge. It then describes a new design knowledge discovery system where design knowledge can be discovered from optimization through an automatic data mining approach. The discovered knowledge has the potential to further help improve the efficiency of the optimization method, thus forming a closed loop of improving optimization and knowledge discovery. The validations of both methods are presented in the context of a case study with parametric form-finding for a nursing unit design with two design objectives: minimizing the nurses’ travel distance and maximizing daylighting performance in patient rooms

Bio-inspired optimization in integrated river basin management

Water resources worldwide are facing severe challenges in terms of quality and quantity. It is essential to conserve, manage, and optimize water resources and their quality through integrated water resources management (IWRM). IWRM is an interdisciplinary field that works on multiple levels to maximize the socio-economic and ecological benefits of water resources. Since this is directly influenced by the river’s ecological health, the point of interest should start at the basin-level. The main objective of this study is to evaluate the application of bio-inspired optimization techniques in integrated river basin management (IRBM). This study demonstrates the application of versatile, flexible and yet simple metaheuristic bio-inspired algorithms in IRBM. In a novel approach, bio-inspired optimization algorithms Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are used to spatially distribute mitigation measures within a basin to reduce long-term annual mean total nitrogen (TN) concentration at the outlet of the basin. The Upper Fuhse river basin developed in the hydrological model, Hydrological Predictions for the Environment (HYPE), is used as a case study. ACO and PSO are coupled with the HYPE model to distribute a set of measures and compute the resulting TN reduction. The algorithms spatially distribute nine crop and subbasin-level mitigation measures under four categories. Both algorithms can successfully yield a discrete combination of measures to reduce long-term annual mean TN concentration. They achieved an 18.65% reduction, and their performance was on par with each other. This study has established the applicability of these bio-inspired optimization algorithms in successfully distributing the TN mitigation measures within the river basin. Stakeholder involvement is a crucial aspect of IRBM. It ensures that researchers and policymakers are aware of the ground reality through large amounts of information collected from the stakeholder. Including stakeholders in policy planning and decision-making legitimizes the decisions and eases their implementation. Therefore, a socio-hydrological framework is developed and tested in the Larqui river basin, Chile, based on a field survey to explore the conditions under which the farmers would implement or extend the width of vegetative filter strips (VFS) to prevent soil erosion. The framework consists of a behavioral, social model (extended Theory of Planned Behavior, TPB) and an agent-based model (developed in NetLogo) coupled with the results from the vegetative filter model (Vegetative Filter Strip Modeling System, VFSMOD-W). The results showed that the ABM corroborates with the survey results and the farmers are willing to extend the width of VFS as long as their utility stays positive. This framework can be used to develop tailor-made policies for river basins based on the conditions of the river basins and the stakeholders' requirements to motivate them to adopt sustainable practices. It is vital to assess whether the proposed management plans achieve the expected results for the river basin and if the stakeholders will accept and implement them. The assessment via simulation tools ensures effective implementation and realization of the target stipulated by the decision-makers. In this regard, this dissertation introduces the application of bio-inspired optimization techniques in the field of IRBM. The successful discrete combinatorial optimization in terms of the spatial distribution of mitigation measures by ACO and PSO and the novel socio-hydrological framework using ABM prove the forte and diverse applicability of bio-inspired optimization algorithms

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Abstract not availableH.R. Maier, Z. Kapelan, Kasprzyk, J. Kollat, L.S. Matott, M.C. Cunha, G.C. Dandy, M.S. Gibbs, E. Keedwell, A. Marchi, A. Ostfeld, D. Savic, D.P. Solomatine, J.A. Vrugt, A.C. Zecchin, B.S. Minsker, E.J. Barbour, G. Kuczera, F. Pasha, A. Castelletti, M. Giuliani, P.M. Ree

On the use of Artificial Neural Networks in Topology Optimisation

The question of how methods from the field of artificial intelligence can help improve the conventional frameworks for topology optimisation has received increasing attention over the last few years. Motivated by the capabilities of neural networks in image analysis, different model-variations aimed at obtaining iteration-free topology optimisation have been proposed with varying success. Other works focused on speed-up through replacing expensive optimisers and state solvers, or reducing the design-space have been attempted, but have not yet received the same attention. The portfolio of articles presenting different applications has as such become extensive, but few real breakthroughs have yet been celebrated. An overall trend in the literature is the strong faith in the "magic" of artificial intelligence and thus misunderstandings about the capabilities of such methods. The aim of this article is therefore to present a critical review of the current state of research in this field. To this end, an overview of the different model-applications is presented, and efforts are made to identify reasons for the overall lack of convincing success. A thorough analysis identifies and differentiates between problematic and promising aspects of existing models. The resulting findings are used to detail recommendations believed to encourage avenues of potential scientific progress for further research within the field.Comment: 36 pages, 7 figures (13 figures counting sub-figures), accepted for publication in Structural and Multidisciplinary Optimizatio

Visualizing Set Relations and Cardinalities Using Venn and Euler Diagrams

In medicine, genetics, criminology and various other areas, Venn and Euler diagrams are used to visualize data set relations and their cardinalities. The data sets are represented by closed curves and the data set relationships are depicted by the overlaps between these curves. Both the sets and their intersections are easily visible as the closed curves are preattentively processed and form common regions that have a strong perceptual grouping effect. Besides set relations such as intersection, containment and disjointness, the cardinality of the sets and their intersections can also be depicted in the same diagram (referred to as area-proportional) through the size of the curves and their overlaps. Size is a preattentive feature and so similarities, differences and trends are easily identified. Thus, such diagrams facilitate data analysis and reasoning about the sets. However, drawing these diagrams manually is difficult, often impossible, and current automatic drawing methods do not always produce appropriate diagrams. This dissertation presents novel automatic drawing methods for different types of Euler diagrams and a user study of how such diagrams can help probabilistic judgement. The main drawing algorithms are: eulerForce, which uses a force-directed approach to lay out Euler diagrams; eulerAPE, which draws area-proportional Venn diagrams with ellipses. The user study evaluated the effectiveness of area- proportional Euler diagrams, glyph representations, Euler diagrams with glyphs and text+visualization formats for Bayesian reasoning, and a method eulerGlyphs was devised to automatically and accurately draw the assessed visualizations for any Bayesian problem. Additionally, analytic algorithms that instantaneously compute the overlapping areas of three general intersecting ellipses are provided, together with an evaluation of the effectiveness of ellipses in drawing accurate area-proportional Venn diagrams for 3-set data and the characteristics of the data that can be depicted accurately with ellipses

Discrete Optimum Design of Cable-Stayed Bridges : Master's Thesis

Ovješeni mostovi su vrlo zahtjevne konstrukcije kod kojih se rasponski sklop ponaša kao kontinuirana greda elastično pridržana pomoću zakrivljenih kabela. Predstavljaju estetski privlačno i učinkovito strukturno rješenje za srednje do velike raspone i naširoko se upotrebljavaju širom svijeta. Ponašanje ovih konstrukcija određeno je krutošću nosivih elemenata (pilona, rasponskog sklopa i vješaljki) i prijenosu sile u vješaljkama. Projektiranje ovješenih mostova je iterativni proces u kojem projektant mora zadovoljiti sve kriterije povezane sa sigurnošću, upotrebom i cijenom mijenjajući određene strukturne parametre. U slučaju ovješenih mostova projekt mosta uključuje rješavanje velikog broja različitih problema kao što su odabir konstrukcijskog sustava, nelinearnost, proces izgradnje, ponašanje konstrukcije pod dinamičkim opterećenjem, itd. Projekt takve konstrukcije generira veliku količinu informacija za vrijeme analize i projektiranja. Optimizacijski algoritam može uključivati kao projektirane varijable mehanička, geometrijska i sekcijska svojstva. Tako one mogu biti upotrijebljene u procesu projektiranja za određivanje poprečnog presjeka strukturnih elemenata i/ili određivanje sile prednapinjanja u kabelima za dobivanje optimalne duljine i visine stupova i raspona. Većina metoda za dobivanje optimalnog rješenja pretpostavlja da su projektirane varijable kontinuiranog tipa. Općenito, projektanti su ograničeni na odabir veličine elemenata iz diskretnog skupa dostupnih veličina i problem u ovom radu je riješen na takav način. Stroga diskretna optimizacija je NP-hard problem (eksponencijalno vrijeme vs polinomsko vrijeme za kontinuiranu optimizaciju) značajno teža nego za kontinuirani problem. U ovom radu prikazana je strukturna analiza i diskretna optimizacija ovješenih mostova. Kao optimizacijska metoda upotrijebljena je segmentalna optimizacijska metoda za dobivanje optimalnih dimenzija poprečnog presjeka ploče i pilona te konačne sile u vješaljkama.Cable-stayed bridges are highly redundant structures in which the deck behaves like a continuous beam elastically supported by the inclined stays. They represent an aesthetically appealing and efficient structural solution for medium-to-long spans and are widely used all over the world. Their behaviour is governed by the stiffness of the load-bearing elements (pylons, deck and cable stays) and the cable force distribution. The structural design of cable-stayed bridges is iterative process in which designers have to satisfy all criteria's relating to safety, use, economy, by changing certain structural parameters. In case of cable-stayed bridges the design of bridge includes solving a lot of different problems such as the choice of structural system, nonlinearity, construction process, dynamic behaviour, etc. Project of such structures generated massive amount of information during analysis and design process. The optimization algorithm can include as design variables mechanical, geometrical and sectional properties. Thus, they can be widely used in design process from dimensioning of cross-sections of structure elements though determine of prestressing force of cable to obtain optimal length and height of towers and spans. Most of the methods for the optimum design of engineering structures make the assumption that member size variables are continuous. Generally, designers are restricted to choosing member sizes from a discrete set of commonly available sizes and this problem is solved here. The rigorous discrete optimum design is a NP-hard problem (exponential time vs polynomial time for continuous optimization) significantly more difficult than the continuous problem. In this work it is presented structural analysis and discrete optimization of concrete cable-stayed bridge. As optimization method is used segmental optimization method to obtain optimal dimensions of deck and tower cross-section and adjustment cable forces