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Alarcon L F, Bastias A

Computer aided strategic planning

Abstract: Modelling concepts developed to analyse project strategic decisions have been extended and implemented in a computer system leading to a generalised methodology that allows modelling and evaluation of strategic decisions in almost any decision area. Some recent application areas of this modelling system are: strategic planning, evaluation of environmental policy impacts and evaluation of risks in owner contractor relationships . The system uses concepts of cross-impact analysis and probabilistic inference as the core of the analysis procedure. A modular model structure and a simplified knowledge acquisition procedure has been designed to avoid the excessive cognitive demands imposed to the users by the original cross-impact methodology. A simple questioning process is used to guide the discussion and elicit information in an ordered manner. The result is a powerful but easy to use computer modelling system where managers, or other potential users, are not exposed to the complexities of the mathematical model. The computer system is implemented in a Windows 95 platform and it provides a graphical interface to help the users in building a conceptual model for the decision problem. The model is a simplified structure of the variables and interactions that influence the decisions being analysed. Influences and interactions assessed by experts or decisions makers are stored in a knowledge base. The system provides powerful analysis capabilities, such as: sensitivity analysis, to identify the most important variables in the decision problem; scenario analysis, to test decision under different environmental conditions; prediction of selected performance outcomes; risk analysis, to identify the risk involved in different alternatives; comparative analysis of the effects of alternative actions on individual or combined performance measures; explanatory capabilities through the model causal structure; etc. The computer model can translate expertise collected from multiple experts into a prediction of significant outcomes for decision-making. The model allows management to test different combinations of options and predict expected performance impacts associated with the decisions under analysis. The use of this decision-support tool can provide valuable insights on alternative options for strategic decision-making

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Full text: content.pdf (360,296 bytes) (available to registered users only)

Series: w78:1998 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.strategies (0.068425) class.impact (0.056619) class.environment (0.054697)
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Permission to reproduce these papers has been graciously provided by Royal Institute of Technology, Stockholm, Sweden. The assistance of the editors, Prof. Bo-Christer Björk and Dr. Adina Jägbeck, is gratefully appreciated.


Ali Touran

A Mathematical Model For Establishing Budget Levels For A Portfolio Of Transit Projects

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Series: w78:2006 (browse)
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Belevicius R, Valentinavicius S, Weener R J

Optimisation of grillage-type foundations

Abstract: The mathematical models for optimisation of grillage-type foundations are presented. Minimising ofmaximum in absolute value vertical reactive force, bending moment, and reaction-bending momenttogether is sought employing methods of finite elements, analytical sensitivity analysis, andmathematical programming. Present models and computer code are implemented in the softwareMatrixFrame. Solutions of a number of problems demonstrate the validity of proposed algorithms.

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Full text: content.pdf (233,114 bytes) (available to registered users only)

Series: ecce:2001 (browse)
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Belousov, V. and Yakovlev, L.

Mathematical Modelling and Electronic Computing Machinery in Town Planning

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Series: w78:1986 (browse)
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Dan H,Yasumuro Y,Ishigaki T,Nishigata T

3d scan planning of outdoor constructions based on photogrammetric model and mathematical optimization

Abstract: A 3D scanner is capable of capturing surface shapes of the objects as a set of point cloud and is extending its applicability toward examining, re-designing and preserving the existing constructions as well as on-site information for BIM. One of the most difficult problems to collect complete surface data of outdoor constructions is to avoid self and mutual occlusions. If we want to collect complete data for covering whole surfaces of the constructions, then we have to measure them from multiple points usually. Moreover, multiple measurements require plenty of time and labor, and each measurement gives a data set consisting of hundreds of millions of 3D points to be processed for further computations. So it is very important to make an effective measurement plan a priori for avoiding redundancy for both labor and computational costs. In this research, therefore, we propose a method for 3D-scan planning of outdoor constructions based on photogrammetric models and mathematical optimization methods. In our proposed method, we first use photogrammetric techniques and make a rough 3D model of measurement scenery: we take photographs of the targets by a calibrated digital camera, and find corresponding characteristic points over the photographs, for example corners and intersection points of edge lines. Next, we triangulate the corresponding points by using 3D photo-modeling software. Finally, we obtain the rough 3D mesh model. After that, we make the optimal scan plan based on the rough 3D mesh model by using some mathematical methods: we examine the visibility and self/mutual occlusion property of each polygon of the 3D mesh, and calculate the minimum number of measurement points and their layout to scan all the surfaces of the targets. Moreover, our proposed method can calculate the optimal layout of the designated number of measurement points to maximize the obtainable data.

Keywords: 3D-Scan Planning,Photogrammetric Model,Mathematical Optimization

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Series: convr:2013 (browse)
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Durmisevic S, Ciftcioglu O, Sariyildiz S

Knowledge modelling of 'soft' data in architectural design

Abstract: IT Context: Information technologies are at present used in various disciplines to address issues such as information processing, data mining, knowledge-modelling etc. Its final goal is to provide necessary aid to professionals during decision-making process. This raises already few questions such as, what type of data is considered and are there some new emerging technologies that can improve knowledge modelling and therefore provide better decision support to the professionals. Design professionals are very often confronted with soft data that they somehow need to interpret and finally integrate in a design. Situations dealing with the numerical data may occur quite naturally in exact sciences like engineering sciences, life sciences etc. However, the quantities subject to consideration in soft sciences are often qualitative rather than quantitative so that we relate to that type of data as 'soft' data. As an example, in such cases, the quantities may be linguistic so that such quantities have to be somehow expressed in numerical form for treatment by conclusive numerical analysis methods. Objectives: The architectural design task is one example having linguistic qualities as priory design information. This is especially the case when qualities of certain space are discussed, like for example in post occupancy evaluation of the buildings, where the relationship between spatial characteristics and psychological aspects plays an important role. Expressions such as: bright colour, light room, large space are some of these examples and therefore a special method is needed for representation and processing of such vague expressions and concepts. Better understanding of these concepts is necessary so that the knowledge can be modelled in a proper way. Methodology: The analyses are performed by means of soft computing methods. The data subject to analysis and later to knowledge modelling belongs to an underground station that is already being used. For this purpose, the data on psychological aspects are obtained via comprehensive inquiry of the users of underground station. For the analysis, the linguistic information is firstly converted to terms in fuzzy logic domain and after appropriate treatment, the data analyses are carried out and the results are expressed in most comprehensible form for design assessments. Such conversions are referred to as fuzzification and defuzzification, where the data are expressed in numerical form and therefore become convenient for mathematical treatment. Conclusions: Referring to the complexity of task in dealing with the soft data as well as dealing with soft computing, the paper first identifies the source of these complexities referring to the architectural design tasks. Following this, a soft computing analysis method based on one case study will be presented, whereby the focus will be on knowledge modelling. Finally, the results of the analyses together with the conclusions regarding the observed effectiveness of the approach are presented.

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Full text: content.pdf (242,586 bytes) (available to registered users only)

Series: w78:2001 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.retrieve (0.036108) class.impact (0.013187) class.analysis (0.007731)
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Permission to reproduce these documents have been graciously provided by CSIR Building and Construction Technology. The assistance of the editors, Mr. Gustav Coetzee and Mr. Frances Boshoff, is gratefully appreciated.


Glisic, M., Samardzic, M. and Lazic, M.

Application of Mathematical Methods While Discovering and Defining Optimal Solutions for Architectural Projects and Construction Subsystems

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Full text: content.pdf (1,093,995 bytes) (available to registered users only)

Series: w78:1986 (browse)
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Jarský C

On an expert system for building process modelling and control

Abstract: The submitted contribution describes the main principles and results of the CONTEC® integratedproject bidding, planning, management and quality control system developed in the last years. Thiscomputer expert system is based on modeling of the building process of erection and the process ofmanagement and maintenance of different structures by use of network diagrams created by anoriginal construction technology network diagram method. This method enables to create and thento use besides classical network graphs different typical network diagrams as models of erection,behavior and maintenance of buildings. Resulting documents describe not only the resulting price,but also the optimum construction or maintenance flow, the cash and resource flow and the qualityassurance question.

Keywords: construction technology, building process, maintenance, network analysis,mathematical model, project management, planning, quality assurance, network diagram, computerexpert systems.

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Full text: content.pdf (297,964 bytes) (available to registered users only)

Series: ecce:2001 (browse)
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Kaka A P

A intelligent knowledge-based system for capturing projects’ performance and initiating tendering strategies

Abstract: "The paper will describe a knowledge-based system developed to capture, process and analyse records of past performance in ordered to help contractors to initiate future strategies and actions. A detailed study of the of a major contractor’s Management Information Systems showed, inter alia, that the “Cost Value Reconciliation” forms (CVR’s), produced on a monthly basis by the contractor’s Surveyor, held a large amount of data unused by the contractors except for the purpose of performance control. Examination of the data revealed that if processed and stored in a central database, it could provide invaluable source of information to contractors for analysing performance and initiating strategies both on the project level and the company level. A subsequent survey of fifteen other contractors revealed that substantially identical CVR procedures were in universal use. It was therefore decided, in order to facilitate the adoption of the proposed system by contractors, to use a CVR format as a data capture facility for the system. Actual CVR sheets used by different contractors were studied, The type of records used in these sheets were examined in terms of their usefulness to management in terms of measuring progress and initiating future actions other than cost control. Further variables that are not currently in use in CVR sheets were introduced. A mathematical model was developed to process these monthly records into useful information subsequently called performance variables (i.e. variables used to measure the contractor’s performance with respect to the project). Finally, further variables were introduces to the system in order to facilitate the sharing of information between different projects. These variables were called Contract Classification Variables (i.e. variables used to describe the project) and contract performance variables) and included nine criteria by which a contract is defined or grouped (e.g. method of tendering, method of procurement etc.). These criteria were identified by contractors as the most important factors influencing contracts’ characteristics and performance. The Contract Performance Variables are the information that can be extracted from the CVR sheets and used to form new strategies (e.g. rate of mark-up on different projects, payment delays etc.). The model was developed in such a way that when a contract is started, the contractor enters the classification and the performance variables in the Individual Project Module. As the contract progresses and actual data become available, the contractor starts to fill the CVR sheets on a monthly basis. When the contract is completed, a the model process the CVR sheets and as a result summarise the performance of the project in terms of the performance variables and the data (including contract classification variables) are sent to the central Database. When a new contract is considered, the contractor defines the project in terms of its classification variables. The model queries the Database for the characteristics of past projects that match the same classification. Once the data is retrieved and processed a set of contract performance variables is predicted for that particular contract. The above method will work as long as adequate similar past projects are found and retrieved from the Database. However, finding adequate data is not always possible, particularly in the early years of applying the proposed model. Also, certain classification variables are not finite in terms of the options available (such as the client for the contract). An Intelligent Data Retrieval system has therefore been developed to overcome this problem. This paper will also explain this system and how the knowledge behind it was elicited."

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Full text: content.pdf (301,794 bytes) (available to registered users only)

Series: w78:2000 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.retrieve (0.022609) class.processing (0.020626) class.analysis (0.019940)
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Permission to reproduce these documents have been graciously provided by Icelandic Building Research Institute. The assistance of the editor, Mr. Gudni Gudnason, is gratefully appreciated


Kilar V

Computer program for linear and nonlinear analysis of tall buildings subjected to horizontal loading

Abstract: In Slovenia, as in many other countries where earthquake or wind loading can be excessive, the stiffness of a tall building is governed by horizontal loading. The paper presents a computer program for linear (static and dynamic) and for nonlinear push-over analysis of symmetric and asymmetric building structures subjected to horizontal loads (such as wind or earthquake loads). The paper briefly describes the used mathematical model and the analysis method for nonlinear static analysis. As an example, the program is used for the nonlinear pushover analysis of several (symmetric and asymmetric) variants of four-storey reinforced- concrete building structure consisted of frames and walls. The results, that are presented in a form of normalized charts, give a valuable information about the nonlinear behavior of different structure variants.

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Series: ecce:1997 (browse)
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