Uses of artificial intelligence in design optimization

International Journal for Numerical Methods in Engineering, 1988

In this two part paper, the problem of implementation of computational algorithms for design optimization into a computer software is discussed. A recently developed algorithm that generates and incorporates approximate second order information about the problem is selected for detailed analyses and discussions. It is shown that numerical behaviour of the algorithm is influenced by variation of the key parameters and procedures. The concept of numerical experiments is introduced, and certain variations of the algorithm and parameters are selected and their influence on its performance is studied. It is shown that the numerical rate of convergence can be substantially improved with proper procedures and values of the parameters. The first part of the paper describes some preliminary analyses and investigations. The second part describes further numerical analyses and detailed procedures for evaluation of performance of various variations of an algorithm or different computer codes. The basic conclusion from the study is that robust and efficient implementation of algorithms requires expert knowledge and considerable numerical experimentation. A wide range of small scale and large scale problems of varying difficulty must be solved to evaluate performance of an algorithm. The study suggests development of knowledge-based systems for practical design optimization.

International Journal of Intelligent Systems, 1992

This article discusses the implementation of a class of design problems in a neural network. The problems, identified at an abstract (i.e., connectivity) level of building design, are characterized as optimization types of problems. Architects often have to generate floor-plan layouts of a building optimized with respect to several points of view, Examples of these points of view, often stated in terms of normative requirements, are the social norms: community, privacy, and circulation-cost. An architectural design problem in the presence of even a single norm from among the above norms is computationally hard and intractable. During the last four decades there have been attempts to automate floor-plan design considering a single norm or a limited number norms. Most of these attempts have traditionally been based on combinatorial enumeration methods, Recent progress in A1 has paved the way for intelligent handling of the architectural design processes using knowledge-based system technology and heuristics programming. This article examines the possibility of the neural networks approach in generating connectivity patterns of building with respect to specific social norms. Our first attempt has been focused on linear-tree type designs with respect to single norms. The idea in this work was borrowed from the Hopfield model of the neural network for implementation of the Traveling Salesman Problem, because of the similarity of our design problems with this problem. Hopfield and other researchers used constant parameters for differentsized problems. Close examination of the network and experiments revealed that this approach does not guarantee a convergence for every case, and chaotic behavior is expected in cases for which the chosen parameters are not appropriate. To overcome this problem this article suggests problem-dependent and problem-size-dependent parameters that vary for each case. Test results from the implementation convey that the approach yields satisfactory results and is worth it to explore its application to other classes of optimization problems. I. THE ARCHITECTURAL DOMAIN An architectural (i.e., building) design process can take place at three different levels: an analytical level, a topological (i.e., connectivity) level, and a geometric level. The first level is analytical in the sense that designers have to deduce requirements of the design from the program of requirements. The topological level is conceptual. At this level the requirements of the design are

The book is aimed at bringing out a comprehensive presentation of Artificial Intelligence (AI) based methodologies and software tools wherein, for the first time, the focus is on addressing a wide spectrum of problems in engineering.

International Journal for Numerical Methods in Engineering, 1983

In this paper a new concept for development of algorithms for optimal design of engineering systems is presented. The basic idea is to use upper and lower bounds on optimum cost to develop iterative search strategies. The main feature of the concept is that it does not rely on one-dimensional search to compute a step size at any design iteration. Implication of the feature is that the algorithms based on this concept require evaluation of constraint functions only once at any design iteration. This is highly desirable for optimal design of engineering systems because evaluation of functions for such systems is very expensive due to their implicit dependence on design variables. An algorithm based on the new concept is derived in the paper. Several new step sizes are introduced and their relation to proper reduced optimal design problems are presented. A new step size based on the constant cost requirement at some design iterations is introduced. Numerical aspects for the algorithm are also presented. Based on the new algorithm, a general-purpose computer code GRP2 is developed. The code is used to solve several problems to gain experience and insight for the algorithm. Numerical experience with examples is discussed. It is concluded that algorithms based on bounding optimum cost have substantial potential for applications in optimal design of engineering systems.

2009

This paper highlights the results of applied techniques, which optimize the design of a pressure vessel for hollow cylinder and hemi-spherical head in terms of the cost of the material and manufacturing. The optimise design problem is tackled in two different stages by creating two different models. The first model will use the simulated annealing technique and the second model uses the tabu search technique. Both of them will use the same minimise cost function equation and the variable vector of this function. That will gain results which could be used in a comparative study for the applied techniques. The study will explain the best solution of these techniques in such work like this. There are two C++ programs were done for the techniques as well.

Solid Mechanics and Its Applications, 2020

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Journal 4 Research - J4R Journal, 2018

Artificial intelligence is the ability of computer systems to perform tasks which otherwise need human brain. Those tasks include visual perception, decision-making, speech recognition and translation between languages. Large amount computing resources is required to traditionally design and optimize complex civil structure in traditional method. This can be effectively eased by using intelligent systems. This paper lists out some of the methods and theories in the application of artificial intelligent systems in the field of civil engineering.

Applied Soft Computing, 2007

Most real world engineering design optimisation approaches reported in the literature aim to find the best set of solutions using computationally expensive quantitative (Q T) models without considering the related qualitative (Q L) effect of the design problem simultaneously. Although, the Q T models provide various detailed information about the design problem, unfortunately, these approaches can result in unrealistic design solutions. This paper presents a soft computing-based integrated design optimisation framework of Q T and Q L search spaces using meta-models (design of experiment, DoE). The proposed approach is applied to multi-objective rod rolling problem with promising results. The paper concludes with a detailed discussion on the relevant issues of integrated Q T and Q L design strategy for design optimisation problems outlining its strengths and challenges.

Mathematical Problems in Engineering, 2013

2003

This paper describes the application of an Intelligent Genetic Design Tool (IGDT) in the design of architectural, structural elements. As a computer design aid an IGDT is innovative in its intelligent interaction with the designer. By always submitting multiple solutions for review by the designer, it is less likely to cause design fixation than other optimization techniques, and allows the user greater range in exploring hard-to-code design criteria such as aesthetics. As an example, the design of a cantilever truss is briefly explored. Using the coded optimization criterion of weight, and the designer's non-coded criteria of visual aesthetics and performance, a series of possible designs are explored. The ability of an IGDT to intelligently respond to the designer's preferences in a way that promotes creative thinking on the part of the designer is demonstrated. A final truss design is selected based on the use of the tool. It is concluded that an IGDT offers a significant...

Proceedings of the International Conference on Knowledge Engineering and Ontology Development, 2009

Analytical aids represent a group of the most widely applied intelligent computer systems for supporting design process. Such systems capture the expertise of a specialist in the application of a design techniquefor instance in the development of an analytical model, in the forming of assumptions or in the interpretation of results. An example discussed here is an "expert" aid to be applied within structural analysis using finite element method. The system is constituted from three modules, one for finite element selection, the other for finite element mesh design and the third one for results" interpretation.

STUDIES IN INFORMATICS AND …, 2006

Abstract: Activities of engineers for design, analysis, manufacturing planning and other purposes constitute a complex structure of decisions. Recently, integrated modeling systems support product lifecycle data management. Model entities are organized in structures by ...

This article explores the applicability of heuristic rules into the decision-making processes involved in design practices, with the aim of generating a strategic approach for the fixation, tangibilization and re-utilization of knowledge within organizations. For this purpose, the research focuses on the creation of a methodological approach and a support tool that seeks to facilitate the introduction of heuristics into particular stages of the design process, such as concept development and architecture definition. This is achieved by providing an initial analysis of the design problem, and the definition of specific problem solving actions based on heuristics. This means that, with the aid of tools specifically developed for the method, the process will help design engineers explore several solution principles with applications previously implemented in diverse domains, thus triggering creativity in problem solving activities. This will enable a more diverse concept generation and a more detailed product development process. In addition, it will allow organizations to work with tools and procedures for them to ensure that emerging knowledge can be integrated to the proposed approach and reused in the future.

1970

The objective of this research was to develop an expert system which chooses the optimum two-dimensional steel structural systems, capable of transferring loads from their points of application to the ground level. This tool will choose from such structural systems as beams, trusses, moment-resistant frames. The type of structures studied in this research are one story buildings which include factories, warehouses, and residences. Several types of loading condition will be considered such as gravity loads (dead, live), lateral loads (wind load, and earthquake). The governing criterion in the choice of the of the most suitable structural system will be to minimize the weight of structure. The study combines analysis, and design of steel structures in a package that chooses the structural system and considers it as a an important variable that affects the optimization of the structure's weight. The choice of the most suitable structural system will be based on using an expert'...

Engineering with Computers, 1988

The present investigation is aimed toward the development of knowledge-based aids for the design of mechanical systems. We have developed and implemented the knowledgebased aid system, which includes MEET and DPMED. The basic approach of MEET follows along the lines of Design = Refinement + Constraint Propagation. This approach has been proven successful in the circuit design domain. Our attempts to utilize MEET have convinced us that we need to extend this methodology to solve mechanical design problems. The DPMED methodology has been applied to design gear-pairs, v-belts, bearings, and shafts. Rules for selecting materials, critical design criteria, and so on are incorporated as part of the rule-system. In order for DPMED to select the design parameter values within the feasible design space, design criteria need to be investigated. Based on these criteria and input/output specifications, DPMED attempts to perform parameter selections. DPMED uses a general hill-climbing algorithm to guide the search.